Deep Learning: Python Deep Learning Masterclass

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AI Sciences,AI Sciences Team

64:18:59

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1 - Introduction

1 - Links for the Courses Materials and Codes.html

2 - Deep LearningDeep Neural Network for Beginners Using Python

2 - Introduction Introduction to Instructor.mp4

02:53

3 - Introduction Introduction to Course.mp4

03:36

4 - Basics of Deep Learning Problem to Solve Part 1.mp4

02:00

5 - Basics of Deep Learning Problem to Solve Part 2.mp4

02:26

6 - Basics of Deep Learning Problem to Solve Part 3.mp4

01:42

7 - Basics of Deep Learning Linear Equation.mp4

03:18

8 - Basics of Deep Learning Linear Equation Vectorized.mp4

03:00

9 - Basics of Deep Learning 3D Feature Space.mp4

03:46

10 - Basics of Deep Learning N Dimensional Space.mp4

02:31

11 - Basics of Deep Learning Theory of Perceptron.mp4

01:46

12 - Basics of Deep Learning Implementing Basic Perceptron.mp4

05:37

13 - Basics of Deep Learning Logical Gates for Perceptrons.mp4

02:46

14 - Basics of Deep Learning Perceptron Training Part 1.mp4

01:40

15 - Basics of Deep Learning Perceptron Training Part 2.mp4

03:41

16 - Basics of Deep Learning Learning Rate.mp4

03:14

17 - Basics of Deep Learning Perceptron Training Part 3.mp4

03:31

18 - Basics of Deep Learning Perceptron Algorithm.mp4

01:00

19 - Basics of Deep Learning Coading Perceptron Algo Data Reading Visualization.mp4

07:22

20 - Basics of Deep Learning Coading Perceptron Algo Perceptron Step.mp4

07:22

21 - Basics of Deep Learning Coading Perceptron Algo Training Perceptron.mp4

06:43

22 - Basics of Deep Learning Coading Perceptron Algo Visualizing the Results.mp4

03:53

23 - Basics of Deep Learning Problem with Linear Solutions.mp4

02:32

24 - Basics of Deep Learning Solution to Problem.mp4

01:03

25 - Basics of Deep Learning Error Functions.mp4

02:21

26 - Basics of Deep Learning Discrete vs Continuous Error Function.mp4

02:25

27 - Basics of Deep Learning Sigmoid Function.mp4

03:01

28 - Basics of Deep Learning MultiClass Problem.mp4

01:18

29 - Basics of Deep Learning Problem of Negative Scores.mp4

03:02

30 - Basics of Deep Learning Need of Softmax.mp4

01:22

31 - Basics of Deep Learning Coding Softmax.mp4

04:06

32 - Basics of Deep Learning One Hot Encoding.mp4

02:41

33 - Basics of Deep Learning Maximum Likelihood Part 1.mp4

05:30

34 - Basics of Deep Learning Maximum Likelihood Part 2.mp4

03:48

35 - Basics of Deep Learning Cross Entropy.mp4

04:06

36 - Basics of Deep Learning Cross Entropy Formulation.mp4

07:38

37 - Basics of Deep Learning Multi Class Cross Entropy.mp4

03:51

38 - Basics of Deep Learning Cross Entropy Implementation.mp4

04:14

39 - Basics of Deep Learning Sigmoid Function Implementation.mp4

00:57

40 - Basics of Deep Learning Output Function Implementation.mp4

02:10

41 - Deep Learning Introduction to Gradient Decent.mp4

05:21

42 - Deep Learning Convex Functions.mp4

02:31

43 - Deep Learning Use of Derivatives.mp4

03:13

44 - Deep Learning How Gradient Decent Works.mp4

03:34

45 - Deep Learning Gradient Step.mp4

01:54

46 - Deep Learning Logistic Regression Algorithm.mp4

01:37

47 - Deep Learning Data Visualization and Reading.mp4

06:11

48 - Deep Learning Updating Weights in Python.mp4

04:14

49 - Deep Learning Implementing Logistic Regression.mp4

12:44

50 - Deep Learning Visualization and Results.mp4

08:43

51 - Deep Learning Gradient Decent vs Perceptron.mp4

04:35

52 - Deep Learning Linear to Non Linear Boundaries.mp4

04:42

53 - Deep Learning Combining Probabilities.mp4

02:07

54 - Deep Learning Weighted Sums.mp4

03:02

55 - Deep Learning Neural Network Architecture.mp4

12:09

56 - Deep Learning Layers and DEEP Networks.mp4

04:44

57 - Deep LearningMulti Class Classification.mp4

02:48

58 - Deep Learning Basics of Feed Forward.mp4

07:51

59 - Deep Learning Feed Forward for DEEP Net.mp4

04:57

60 - Deep Learning Deep Learning Algo Overview.mp4

01:57

61 - Deep Learning Basics of Back Propagation.mp4

06:33

62 - Deep Learning Updating Weights.mp4

02:46

63 - Deep Learning Chain Rule for BackPropagation.mp4

05:53

64 - Deep Learning Sigma Prime.mp4

02:23

65 - Deep Learning Data Analysis NN Implementation.mp4

05:25

66 - Deep Learning One Hot Encoding NN Implementation.mp4

03:11

67 - Deep Learning Scaling the Data NN Implementation.mp4

01:48

68 - Deep Learning Splitting the Data NN Implementation.mp4

04:55

69 - Deep Learning Helper Functions NN Implementation.mp4

02:18

70 - Deep Learning Training NN Implementation.mp4

12:25

71 - Deep Learning Testing NN Implementation.mp4

03:21

72 - Optimizations Underfitting vs Overfitting.mp4

05:19

73 - Optimizations Early Stopping.mp4

03:51

74 - Optimizations Quiz.mp4

00:58

75 - Optimizations Solution Regularization.mp4

05:59

76 - Optimizations L1 L2 Regularization.mp4

03:13

77 - Optimizations Dropout.mp4

02:59

78 - Optimizations Local Minima Problem.mp4

02:55

79 - Optimizations Random Restart Solution.mp4

04:27

81 - Optimizations Other Activation Functions.mp4

03:19

82 - Final Project Final Project Part 1.mp4

11:20

83 - Final Project Final Project Part 2.mp4

13:16

84 - Final Project Final Project Part 3.mp4

12:58

85 - Final Project Final Project Part 4.mp4

12:19

86 - Final Project Final Project Part 5.mp4

08:06

3 - Deep Learning CNN Convolutional Neural Networks with Python

87 - Link to Github to get the Python Notebooks.html

88 - Introduction Instructor Introduction.mp4

02:19

89 - Introduction Why CNN.mp4

07:00

90 - Introduction Focus of the Course.mp4

07:12

91 - Image Processing Gray Scale Images.mp4

07:21

92 - Image Processing Gray Scale Images Quiz.mp4

00:27

93 - Image Processing Gray Scale Images Solution.mp4

00:48

94 - Image Processing RGB Images.mp4

07:35

95 - Image Processing RGB Images Quiz.mp4

00:36

96 - Image Processing RGB Images Solution.mp4

00:45

97 - Image Processing Reading and Showing Images in Python.mp4

09:24

98 - Image Processing Reading and Showing Images in Python Quiz.mp4

00:22

99 - Image Processing Reading and Showing Images in Python Solution.mp4

00:30

100 - Image Processing Converting an Image to Grayscale in Python.mp4

07:55

101 - Image Processing Converting an Image to Grayscale in Python Quiz.mp4

00:35

102 - Image Processing Converting an Image to Grayscale in Python Solution.mp4

00:58

103 - Image Processing Image Formation.mp4

05:37

104 - Image Processing Image Formation Quiz.mp4

00:31

105 - Image Processing Image Formation Solution.mp4

00:33

106 - Image Processing Image Blurring 1.mp4

10:47

107 - Image Processing Image Blurring 1 Quiz.mp4

00:43

108 - Image Processing Image Blurring 1 Solution.mp4

00:29

109 - Image Processing Image Blurring 2.mp4

08:23

110 - Image Processing Image Blurring 2 Quiz.mp4

00:29

111 - Image Processing Image Blurring 2 Solution.mp4

00:47

112 - Image Processing General Image Filtering.mp4

04:48

113 - Image Processing Convolution.mp4

05:13

114 - Image Processing Edge Detection.mp4

06:43

115 - Image Processing Image Sharpening.mp4

03:40

116 - Image Processing Implementation of Image Blurring Edge Detection Image Sharpening in Python.mp4

16:54

117 - Image Processing Parameteric Shape Detection.mp4

07:42

118 - Image Processing Image Processing Activity.mp4

03:48

119 - Image Processing Image Processing Activity Solution.mp4

12:03

120 - Object Detection Introduction to Object Detection.mp4

06:38

121 - Object Detection Classification PipleLine.mp4

10:59

122 - Object Detection Classification PipleLine Quiz.mp4

00:23

123 - Object Detection Classification PipleLine Solution.mp4

00:40

124 - Object Detection Sliding Window Implementation.mp4

07:19

125 - Object Detection Shift Scale Rotation Invariance.mp4

09:41

126 - Object Detection Shift Scale Rotation Invariance Exercise.mp4

15:38

127 - Object Detection Person Detection.mp4

09:42

128 - Object Detection HOG Features.mp4

07:02

129 - Object Detection HOG Features Exercise.mp4

10:50

130 - Object Detection Hand Engineering vs CNNs.mp4

08:40

131 - Object Detection Object Detection Activity.mp4

04:52

132 - Deep Neural Network Overview Neuron and Perceptron.mp4

10:39

133 - Deep Neural Network Overview DNN Architecture.mp4

07:30

134 - Deep Neural Network Overview DNN Architecture Quiz.mp4

00:50

135 - Deep Neural Network Overview DNN Architecture Solution.mp4

01:11

136 - Deep Neural Network Overview FeedForward FullyConnected MLP.mp4

04:26

137 - Deep Neural Network Overview Calculating Number of Weights of DNN.mp4

06:04

138 - Deep Neural Network Overview Calculating Number of Weights of DNN Quiz.mp4

00:22

139 - Deep Neural Network Overview Calculating Number of Weights of DNN Solution.mp4

00:59

140 - Deep Neural Network Overview Number of Nuerons vs Number of Layers.mp4

08:26

141 - Deep Neural Network Overview Discriminative vs Generative Learning.mp4

05:11

142 - Deep Neural Network Overview Universal Approximation Therorem.mp4

06:20

143 - Deep Neural Network Overview Why Depth.mp4

04:14

144 - Deep Neural Network Overview Decision Boundary in DNN.mp4

05:48

145 - Deep Neural Network Overview Decision Boundary in DNN Quiz.mp4

00:52

146 - Deep Neural Network Overview Decision Boundary in DNN Solution.mp4

02:46

147 - Deep Neural Network Overview BiasTerm.mp4

05:12

148 - Deep Neural Network Overview BiasTerm Quiz.mp4

00:29

149 - Deep Neural Network Overview BiasTerm Solution.mp4

00:52

150 - Deep Neural Network Overview Activation Function.mp4

08:13

151 - Deep Neural Network Overview Activation Function Quiz.mp4

00:36

152 - Deep Neural Network Overview Activation Function Solution.mp4

01:11

153 - Deep Neural Network Overview DNN Training Parameters.mp4

11:00

154 - Deep Neural Network Overview DNN Training Parameters Quiz.mp4

00:36

155 - Deep Neural Network Overview DNN Training Parameters Solution.mp4

00:42

156 - Deep Neural Network Overview Gradient Descent.mp4

08:12

157 - Deep Neural Network Overview BackPropagation.mp4

11:07

158 - Deep Neural Network Overview Training DNN Animantion.mp4

03:42

159 - Deep Neural Network Overview Weigth Initialization.mp4

09:25

160 - Deep Neural Network Overview Weigth Initialization Quiz.mp4

00:38

161 - Deep Neural Network Overview Weigth Initialization Solution.mp4

01:01

162 - Deep Neural Network Overview Batch miniBatch Stocastic Gradient Descent.mp4

08:34

163 - Deep Neural Network Overview Batch Normalization.mp4

05:28

164 - Deep Neural Network Overview Rprop and Momentum.mp4

12:26

165 - Deep Neural Network Overview Rprop and Momentum Quiz.mp4

01:05

166 - Deep Neural Network Overview Rprop and Momentum Solution.mp4

01:14

167 - Deep Neural Network Overview Convergence Animation.mp4

03:39

168 - Deep Neural Network Overview DropOut Early Stopping and Hyperparameters.mp4

13:39

169 - Deep Neural Network Overview DropOut Early Stopping and Hyperparameters Quiz.mp4

01:08

170 - Deep Neural Network Overview DropOut Early Stopping and Hyperparameters Solution.mp4

02:20

171 - Deep Neural Network Architecture Convolution Revisited.mp4

08:16

172 - Deep Neural Network Architecture Implementing Convolution in Python Revisited.mp4

07:07

173 - Deep Neural Network Architecture Why Convolution.mp4

07:02

174 - Deep Neural Network Architecture Filters Padding Strides.mp4

08:04

175 - Deep Neural Network Architecture Padding Image.mp4

10:36

176 - Deep Neural Network Architecture Pooling Tensors.mp4

06:25

177 - Deep Neural Network Architecture CNN Example.mp4

07:04

178 - Deep Neural Network Architecture Convolution and Pooling Details.mp4

08:30

179 - Deep Neural Network Architecture Maxpooling Exercise.mp4

04:11

180 - Deep Neural Network Architecture NonVectorized Implementations of Conv2d and Pool2d.mp4

18:59

181 - Deep Neural Network Architecture Deep Neural Network Architecture Activity.mp4

02:28

182 - Gradient Descent in CNNs Example Setup.mp4

09:15

183 - Gradient Descent in CNNs Why Derivaties.mp4

10:28

184 - Gradient Descent in CNNs Why Derivaties Quiz.mp4

00:54

185 - Gradient Descent in CNNs Why Derivaties Solution.mp4

03:05

186 - Gradient Descent in CNNs What is Chain Rule.mp4

07:58

187 - Gradient Descent in CNNs Applying Chain Rule.mp4

09:05

188 - Gradient Descent in CNNs Gradients of MaxPooling Layer.mp4

08:20

189 - Gradient Descent in CNNs Gradients of MaxPooling Layer Quiz.mp4

00:57

190 - Gradient Descent in CNNs Gradients of MaxPooling Layer Solution.mp4

01:48

191 - Gradient Descent in CNNs Gradients of Convolutional Layer.mp4

09:01

192 - Gradient Descent in CNNs Extending To Multiple Filters.mp4

05:25

193 - Gradient Descent in CNNs Extending to Multiple Layers.mp4

06:50

194 - Gradient Descent in CNNs Extending to Multiple Layers Quiz.mp4

01:24

195 - Gradient Descent in CNNs Extending to Multiple Layers Solution.mp4

05:41

196 - Gradient Descent in CNNs Implementation in Numpy ForwardPass.mp4

08:20

197 - Gradient Descent in CNNs Implementation in Numpy BackwardPass 1.mp4

06:47

198 - Gradient Descent in CNNs Implementation in Numpy BackwardPass 2.mp4

04:37

199 - Gradient Descent in CNNs Implementation in Numpy BackwardPass 3.mp4

09:07

200 - Gradient Descent in CNNs Implementation in Numpy BackwardPass 4.mp4

12:21

201 - Gradient Descent in CNNs Implementation in Numpy BackwardPass 5.mp4

19:41

202 - Gradient Descent in CNNs Gradient Descent in CNNs Activity.mp4

02:00

203 - Introduction to TensorFlow Introduction.mp4

09:57

204 - Introduction to TensorFlow FashionMNIST Example Plan Neural Network.mp4

22:44

205 - Introduction to TensorFlow FashionMNIST Example CNN.mp4

20:04

206 - Introduction to TensorFlow Introduction to TensorFlow Activity.mp4

01:24

207 - Classical CNNs LeNet.mp4

07:24

208 - Classical CNNs LeNet Quiz.mp4

01:05

209 - Classical CNNs LeNet Solution.mp4

01:50

210 - Classical CNNs AlexNet.mp4

09:31

211 - Classical CNNs VGG.mp4

05:54

212 - Classical CNNs InceptionNet.mp4

08:11

213 - Classical CNNs GoogLeNet.mp4

05:59

214 - Classical CNNs Resnet.mp4

09:56

215 - Classical CNNs Classical CNNs Activity.mp4

01:39

216 - Transfer Learning What is Transfer learning.mp4

05:03

217 - Transfer Learning Why Transfer Learning.mp4

04:26

218 - Transfer Learning Practical Tips.mp4

07:10

219 - Transfer Learning Project in TensorFlow.mp4

38:03

220 - Transfer Learning ImageNet Challenge.mp4

03:53

221 - Transfer Learning Transfer Learning Activity.mp4

01:11

222 - Yolo Image Classfication Revisited.mp4

05:05

223 - Yolo Sliding Window Object Localization.mp4

06:36

224 - Yolo Sliding Window Efficient Implementation.mp4

06:59

225 - Yolo Yolo Introduction.mp4

07:07

226 - Yolo Yolo Training Data Generation.mp4

06:15

227 - Yolo Yolo Anchor Boxes.mp4

08:34

228 - Yolo Yolo Algorithm.mp4

06:06

229 - Yolo Yolo Non Maxima Supression.mp4

05:22

230 - Yolo RCNN.mp4

04:11

231 - Yolo Yolo Activity.mp4

01:45

232 - Face Verification Problem Setup.mp4

06:35

233 - Face Verification Project Implementation.mp4

21:27

234 - Face Verification Face Verification Activity.mp4

00:57

235 - Neural Style Transfer Problem Setup.mp4

10:32

236 - Neural Style Transfer Implementation Tensorflow Hub.mp4

08:44

4 - Deep Learning Recurrent Neural Networks with Python

237 - Link to oneDrive and Github to get the Python Notebooks.html

238 - Introduction Introduction to Instructor and Aisciences.mp4

12:18

239 - Introduction Introduction To Instructor.mp4

02:19

240 - Introduction Focus of the Course.mp4

08:55

241 - Applications of RNN Motivation Human Activity Recognition.mp4

08:05

242 - Applications of RNN Motivation Image Captioning.mp4

05:51

243 - Applications of RNN Motivation Machine Translation.mp4

07:56

244 - Applications of RNN Motivation Speech Recognition.mp4

05:31

245 - Applications of RNN Motivation Stock Price Predictions.mp4

05:58

246 - Applications of RNN Motivation When to Model RNN.mp4

18:47

247 - Applications of RNN Motivation Activity.mp4

03:19

248 - DNN Overview Why PyTorch.mp4

04:17

249 - DNN Overview PyTorch Installation and Tensors Introduction.mp4

10:32

250 - DNN Overview Automatic Diffrenciation Pytorch New.mp4

07:36

251 - DNN Overview Why DNNs in Machine Learning.mp4

04:13

252 - DNN Overview Representational Power and Data Utilization Capacity of DNN.mp4

07:13

253 - DNN Overview Perceptron.mp4

05:08

254 - DNN Overview Perceptron Exercise.mp4

02:36

255 - DNN Overview Perceptron Exercise Solution.mp4

03:16

256 - DNN Overview Perceptron Implementation.mp4

07:26

257 - DNN Overview DNN Architecture.mp4

03:52

258 - DNN Overview DNN Architecture Exercise.mp4

02:06

259 - DNN Overview DNN Architecture Exercise Solution.mp4

04:33

260 - DNN Overview DNN ForwardStep Implementation.mp4

08:21

261 - DNN Overview DNN Why Activation Function Is Required.mp4

04:47

262 - DNN Overview DNN Why Activation Function Is Required Exercise.mp4

01:48

263 - DNN Overview DNN Why Activation Function Is Required Exercise Solution.mp4

03:39

264 - DNN Overview DNN Properties Of Activation Function.mp4

06:04

265 - DNN Overview DNN Activation Functions In Pytorch.mp4

03:49

266 - DNN Overview DNN What Is Loss Function.mp4

07:10

267 - DNN Overview DNN What Is Loss Function Exercise.mp4

00:58

268 - DNN Overview DNN What Is Loss Function Exercise Solution.mp4

04:25

269 - DNN Overview DNN What Is Loss Function Exercise 02.mp4

00:54

270 - DNN Overview DNN What Is Loss Function Exercise 02 Solution.mp4

03:15

271 - DNN Overview DNN Loss Function In Pytorch.mp4

05:45

272 - DNN Overview DNN Gradient Descent.mp4

05:58

273 - DNN Overview DNN Gradient Descent Exercise.mp4

03:03

274 - DNN Overview DNN Gradient Descent Exercise Solution.mp4

04:15

275 - DNN Overview DNN Gradient Descent Implementation.mp4

06:51

276 - DNN Overview DNN Gradient Descent Stochastic Batch Minibatch.mp4

07:07

277 - DNN Overview DNN Implemenation Gradient Step.mp4

04:02

278 - DNN Overview DNN Implemenation Stochastic Gradient Descent.mp4

13:53

279 - DNN Overview DNN Gradient Descent Summary.mp4

02:38

280 - DNN Overview DNN Implemenation Batch Gradient Descent.mp4

06:46

281 - DNN Overview DNN Implemenation Minibatch Gradient Descent.mp4

09:04

282 - DNN Overview DNN Implemenation In PyTorch.mp4

15:19

283 - DNN Overview DNN Weights Initializations.mp4

04:35

284 - DNN Overview DNN Learning Rate.mp4

04:03

285 - DNN Overview DNN Batch Normalization.mp4

02:05

286 - DNN Overview DNN batch Normalization Implementation.mp4

02:41

287 - DNN Overview DNN Optimizations.mp4

04:08

288 - DNN Overview DNN Dropout.mp4

03:58

289 - DNN Overview DNN Dropout In PyTorch.mp4

02:03

290 - DNN Overview DNN Early Stopping.mp4

03:34

291 - DNN Overview DNN Hyperparameters.mp4

03:33

292 - DNN Overview DNN Pytorch CIFAR10 Example.mp4

15:56

293 - RNN Architecture Introduction to Module.mp4

05:42

294 - RNN Architecture Fixed Length Memory Model.mp4

10:06

295 - RNN Architecture Fixed Length Memory Model Exercise.mp4

00:46

296 - RNN Architecture Fixed Length Memory Model Exercise Solution Part 01.mp4

03:37

297 - RNN Architecture Fixed Length Memory Model Exercise Solution Part 02.mp4

03:54

298 - RNN Architecture Infinite Memory Architecture.mp4

10:44

299 - RNN Architecture Infinite Memory Architecture Exercise.mp4

01:07

300 - RNN Architecture Infinite Memory Architecture Solution.mp4

04:45

301 - RNN Architecture Weight Sharing.mp4

14:51

302 - RNN Architecture Notations.mp4

08:49

303 - RNN Architecture ManyToMany Model.mp4

11:57

304 - RNN Architecture ManyToMany Model Exercise 01.mp4

02:05

305 - RNN Architecture ManyToMany Model Solution 01.mp4

02:40

306 - RNN Architecture ManyToMany Model Exercise 02.mp4

00:49

307 - RNN Architecture ManyToMany Model Solution 02.mp4

03:20

308 - RNN Architecture ManyToOne Model.mp4

07:57

309 - RNN Architecture OneToMany Model Exercise.mp4

00:32

310 - RNN Architecture OneToMany Model Solution.mp4

02:31

311 - RNN Architecture OneToMany Model.mp4

05:56

312 - RNN Architecture ManyToOne Model Exercise.mp4

01:49

313 - RNN Architecture ManyToOne Model Solution.mp4

01:22

314 - RNN Architecture Activity Many to One.mp4

06:47

315 - RNN Architecture Activity Many to One Exercise.mp4

00:40

316 - RNN Architecture Activity Many to One Solution.mp4

01:50

317 - RNN Architecture ManyToMany Different Sizes Model.mp4

09:07

318 - RNN Architecture Activity Many to Many Nmt.mp4

04:50

319 - RNN Architecture Models Summary.mp4

03:34

320 - RNN Architecture Deep RNNs.mp4

08:13

321 - RNN Architecture Deep RNNs Exercise.mp4

00:51

322 - RNN Architecture Deep RNNs Solution.mp4

02:50

323 - Gradient Decsent in RNN Introduction to Gradient Descent Module.mp4

07:51

324 - Gradient Decsent in RNN Example Setup.mp4

08:20

325 - Gradient Decsent in RNN Equations.mp4

06:03

326 - Gradient Decsent in RNN Equations Exercise.mp4

01:45

327 - Gradient Decsent in RNN Equations Solution.mp4

02:14

328 - Gradient Decsent in RNN Loss Function.mp4

08:06

329 - Gradient Decsent in RNN Why Gradients.mp4

06:06

330 - Gradient Decsent in RNN Why Gradients Exercise.mp4

00:26

331 - Gradient Decsent in RNN Why Gradients Solution.mp4

02:49

332 - Gradient Decsent in RNN Chain Rule.mp4

07:28

333 - Gradient Decsent in RNN Chain Rule in Action.mp4

05:58

334 - Gradient Decsent in RNN BackPropagation Through Time.mp4

09:37

335 - Gradient Decsent in RNN Activity.mp4

02:19

336 - RNN implementation Automatic Diffrenciation.mp4

04:07

337 - RNN implementation Automatic Diffrenciation Pytorch.mp4

08:26

338 - RNN implementation Language Modeling Next Word Prediction Vocabulary Index.mp4

04:04

339 - RNN implementation Language Modeling Next Word Prediction Vocabulary Index Embeddings.mp4

03:16

340 - RNN implementation Language Modeling Next Word Prediction RNN Architecture.mp4

04:09

341 - RNN implementation Language Modeling Next Word Prediction Python 1.mp4

07:12

342 - RNN implementation Language Modeling Next Word Prediction Python 2.mp4

09:02

343 - RNN implementation Language Modeling Next Word Prediction Python 3.mp4

07:27

344 - RNN implementation Language Modeling Next Word Prediction Python 4.mp4

05:33

345 - RNN implementation Language Modeling Next Word Prediction Python 5.mp4

04:35

346 - RNN implementation Language Modeling Next Word Prediction Python 6.mp4

13:34

347 - Sentiment Classification using RNN Vocabulary Implementation.mp4

09:46

348 - Sentiment Classification using RNN Vocabulary Implementation Helpers.mp4

05:50

349 - Sentiment Classification using RNN Vocabulary Implementation From File.mp4

06:26

350 - Sentiment Classification using RNN Vectorizer.mp4

05:17

351 - Sentiment Classification using RNN RNN Setup 1.mp4

07:20

352 - Sentiment Classification using RNN RNN Setup 2.mp4

03:27

353 - Sentiment Classification using RNN WhatNext.mp4

03:27

354 - Vanishing Gradients in RNN Introduction to Better RNNs Module.mp4

07:23

355 - Vanishing Gradients in RNN Introduction Vanishing Gradients in RNN.mp4

07:52

356 - Vanishing Gradients in RNN GRU.mp4

11:59

357 - Vanishing Gradients in RNN GRU Optional.mp4

06:08

358 - Vanishing Gradients in RNN LSTM.mp4

08:44

359 - Vanishing Gradients in RNN LSTM Optional.mp4

06:04

360 - Vanishing Gradients in RNN Bidirectional RNN.mp4

08:23

361 - Vanishing Gradients in RNN Attention Model.mp4

10:31

362 - Vanishing Gradients in RNN Attention Model Optional.mp4

06:34

363 - TensorFlow Introduction to TensorFlow.mp4

09:57

364 - TensorFlow TensorFlow Text Classification Example using RNN.mp4

25:55

365 - Project I Book Writer Introduction.mp4

12:15

366 - Project I Book Writer Data Mapping.mp4

14:59

367 - Project I Book Writer Modling RNN Architecture.mp4

17:52

368 - Project I Book Writer Modling RNN Model in TensorFlow.mp4

11:15

369 - Project I Book Writer Modling RNN Model Training.mp4

07:47

370 - Project I Book Writer Modling RNN Model Text Generation.mp4

13:28

371 - Project I Book Writer Activity.mp4

07:44

372 - Project II Stock Price Prediction Problem Statement.mp4

06:06

373 - Project II Stock Price Prediction Data Set.mp4

11:53

374 - Project II Stock Price Prediction Data Prepration.mp4

19:06

375 - Project II Stock Price Prediction RNN Model Training and Evaluation.mp4

20:05

376 - Project II Stock Price Prediction Activity.mp4

06:15

377 - Further Readings and Resourses Further Readings and Resourses 1.mp4

10:30

5 - NLPNatural Language Processing in PythonTheory Projects

378 - Links for the Courses Materials and Codes.html

379 - Introduction Introduction to Course.mp4

00:55

380 - Introduction Introduction to Instructor.mp4

05:44

381 - Introduction Introduction to CoInstructor.mp4

01:30

382 - Introduction Course Introduction.mp4

11:16

383 - IntroductionRegular Expressions What Is Regular Expression.mp4

05:56

384 - IntroductionRegular Expressions Why Regular Expression.mp4

06:31

385 - IntroductionRegular Expressions ELIZA Chatbot.mp4

04:23

386 - IntroductionRegular Expressions Python Regular Expression Package.mp4

04:24

387 - Meta CharactersRegular Expressions Meta Characters.mp4

02:27

388 - Meta CharactersRegular Expressions Meta Characters Bigbrackets Exercise.mp4

04:19

389 - Meta CharactersRegular Expressions Meta Characters Bigbrackets Exercise Solution.mp4

03:59

390 - Meta CharactersRegular Expressions Meta Characters Bigbrackets Exercise 2.mp4

02:11

391 - Meta CharactersRegular Expressions Meta Characters Bigbrackets Exercise 2 Solution.mp4

04:37

392 - Meta CharactersRegular Expressions Meta Characters Cap.mp4

03:18

393 - Meta CharactersRegular Expressions Meta Characters Cap Exercise 3.mp4

02:03

394 - Meta CharactersRegular Expressions Meta Characters Cap Exercise 3 Solution.mp4

04:44

395 - Meta CharactersRegular Expressions Backslash.mp4

05:02

396 - Meta CharactersRegular Expressions Backslash Continued.mp4

07:59

397 - Meta CharactersRegular Expressions Backslash Continued 01.mp4

03:51

398 - Meta CharactersRegular Expressions Backslash Squared Brackets Exercise.mp4

01:38

399 - Meta CharactersRegular Expressions Backslash Squared Brackets Exercise Solution.mp4

03:59

400 - Meta CharactersRegular Expressions Backslash Squared Brackets Exercise Another Solution.mp4

04:43

401 - Meta CharactersRegular Expressions Backslash Exercise.mp4

01:43

402 - Meta CharactersRegular Expressions Backslash Exercise Solution And Special Sequences Exercise.mp4

05:12

403 - Meta CharactersRegular Expressions Solution And Special Sequences Exercise Solution.mp4

04:57

404 - Meta CharactersRegular Expressions Meta Character Asterisk.mp4

05:18

405 - Meta CharactersRegular Expressions Meta Character Asterisk Exercise.mp4

04:54

406 - Meta CharactersRegular Expressions Meta Character Asterisk Exercise Solution.mp4

05:04

407 - Meta CharactersRegular Expressions Meta Character Asterisk Homework.mp4

04:28

408 - Meta CharactersRegular Expressions Meta Character Asterisk Greedymatching.mp4

05:54

409 - Meta CharactersRegular Expressions Meta Character Plus And Questionmark.mp4

05:46

410 - Meta CharactersRegular Expressions Meta Character Curly Brackets Exercise.mp4

03:25

411 - Meta CharactersRegular Expressions Meta Character Curly Brackets Exercise Solution.mp4

05:18

412 - Pattern Objects Pattern Objects.mp4

05:05

413 - Pattern Objects Pattern Objects Match Method Exersize.mp4

02:43

414 - Pattern Objects Pattern Objects Match Method Exersize Solution.mp4

07:11

415 - Pattern Objects Pattern Objects Match Method Vs Search Method.mp4

05:18

416 - Pattern Objects Pattern Objects Finditer Method.mp4

03:20

417 - Pattern Objects Pattern Objects Finditer Method Exersize Solution.mp4

06:22

418 - More Meta Characters Meta Characters Logical Or.mp4

06:29

419 - More Meta Characters Meta Characters Beginning And End Patterns.mp4

04:57

420 - More Meta Characters Meta Characters Paranthesis.mp4

07:03

421 - String Modification String Modification.mp4

03:49

422 - String Modification Word Tokenizer Using Split Method.mp4

04:34

423 - String Modification Sub Method Exercise.mp4

04:44

424 - String Modification Sub Method Exercise Solution.mp4

04:30

425 - Words and Tokens What Is A Word.mp4

04:41

426 - Words and Tokens Definition Of Word Is Task Dependent.mp4

05:20

427 - Words and Tokens Vocabulary And Corpus.mp4

05:38

428 - Words and Tokens Tokens.mp4

03:14

429 - Words and Tokens Tokenization In Spacy.mp4

09:10

430 - Sentiment Classification Yelp Reviews Classification Mini Project Introduction.mp4

05:35

431 - Sentiment Classification Yelp Reviews Classification Mini Project Vocabulary Initialization.mp4

06:48

432 - Sentiment Classification Yelp Reviews Classification Mini Project Adding Tokens To Vocabulary.mp4

04:54

433 - Sentiment Classification Yelp Reviews Classification Mini Project Look Up Functions In Vocabulary.mp4

05:57

434 - Sentiment Classification Yelp Reviews Classification Mini Project Building Vocabulary From Data.mp4

09:17

435 - Sentiment Classification Yelp Reviews Classification Mini Project One Hot Encoding.mp4

06:51

436 - Sentiment Classification Yelp Reviews Classification Mini Project One Hot Encoding Implementation.mp4

09:47

437 - Sentiment Classification Yelp Reviews Classification Mini Project Encoding Documents.mp4

06:50

438 - Sentiment Classification Yelp Reviews Classification Mini Project Encoding Documents Implementation.mp4

06:28

439 - Sentiment Classification Yelp Reviews Classification Mini Project Train Test Splits.mp4

04:20

440 - Sentiment Classification Yelp Reviews Classification Mini Project Featurecomputation.mp4

06:08

441 - Sentiment Classification Yelp Reviews Classification Mini Project Classification.mp4

10:45

442 - Language Independent Tokenization Tokenization In Detial Introduction.mp4

04:28

443 - Language Independent Tokenization Tokenization Is Hard.mp4

05:16

444 - Language Independent Tokenization Tokenization Byte Pair Encoding.mp4

06:08

445 - Language Independent Tokenization Tokenization Byte Pair Encoding Example.mp4

08:33

446 - Language Independent Tokenization Tokenization Byte Pair Encoding On Test Data.mp4

07:14

447 - Language Independent Tokenization Tokenization Byte Pair Encoding Implementation Getpaircounts.mp4

08:11

448 - Language Independent Tokenization Tokenization Byte Pair Encoding Implementation Mergeincorpus.mp4

07:49

449 - Language Independent Tokenization Tokenization Byte Pair Encoding Implementation BFE Training.mp4

06:10

450 - Language Independent Tokenization Tokenization Byte Pair Encoding Implementation BFE Encoding.mp4

06:25

451 - Language Independent Tokenization Tokenization Byte Pair Encoding Implementation BFE Encoding One Pair.mp4

09:11

452 - Language Independent Tokenization Tokenization Byte Pair Encoding Implementation BFE Encoding One Pair 1.mp4

07:53

453 - Text Nomalization Word Normalization Case Folding.mp4

04:43

454 - Text Nomalization Word Normalization Lematization.mp4

06:48

455 - Text Nomalization Word Normalization Stemming.mp4

02:31

456 - Text Nomalization Word Normalization Sentence Segmentation.mp4

06:27

457 - String Matching and Spelling Correction Spelling Correction Minimum Edit Distance Intro.mp4

07:59

458 - String Matching and Spelling Correction Spelling Correction Minimum Edit Distance Example.mp4

09:04

459 - String Matching and Spelling Correction Spelling Correction Minimum Edit Distance Table Filling.mp4

09:10

460 - String Matching and Spelling Correction Spelling Correction Minimum Edit Distance Dynamic Programming.mp4

07:17

461 - String Matching and Spelling Correction Spelling Correction Minimum Edit Distance Psudocode.mp4

03:55

462 - String Matching and Spelling Correction Spelling Correction Minimum Edit Distance Implementation.mp4

06:57

463 - String Matching and Spelling Correction Spelling Correction Minimum Edit Distance Implementation Bugfixing.mp4

02:40

464 - String Matching and Spelling Correction Spelling Correction Implementation.mp4

07:42

465 - Language Modeling What Is A Language Model.mp4

05:50

466 - Language Modeling Language Model Formal Definition.mp4

06:31

467 - Language Modeling Language Model Curse Of Dimensionality.mp4

04:27

468 - Language Modeling Language Model Markov Assumption And NGrams.mp4

07:06

469 - Language Modeling Language Model Implementation Setup.mp4

04:24

470 - Language Modeling Language Model Implementation Ngrams Function.mp4

08:42

471 - Language Modeling Language Model Implementation Update Counts Function.mp4

05:46

472 - Language Modeling Language Model Implementation Probability Model Funciton.mp4

06:35

473 - Language Modeling Language Model Implementation Reading Corpus.mp4

12:17

474 - Language Modeling Language Model Implementation Sampling Text.mp4

18:17

475 - Topic Modelling with Word and Document Representations One Hot Vectors.mp4

04:10

476 - Topic Modelling with Word and Document Representations One Hot Vectors Implementaton.mp4

05:42

477 - Topic Modelling with Word and Document Representations One Hot Vectors Limitations.mp4

04:45

478 - Topic Modelling with Word and Document Representations One Hot Vectors Uses As Target Labeling.mp4

03:42

479 - Topic Modelling with Word and Document Representations Term Frequency For Document Representations.mp4

03:12

480 - Topic Modelling with Word and Document Representations Term Frequency For Document Representations Implementations.mp4

05:31

481 - Topic Modelling with Word and Document Representations Term Frequency For Word Representations.mp4

05:17

482 - Topic Modelling with Word and Document Representations TFIDF For Document Representations.mp4

05:01

483 - Topic Modelling with Word and Document Representations TFIDF For Document Representations Implementation Reading Corpus.mp4

04:24

485 - Topic Modelling with Word and Document Representations TFIDF For Document Representations Implementation Computing TFIDF.mp4

07:22

486 - Topic Modelling with Word and Document Representations Topic Modeling With TFIDF 1.mp4

04:20

487 - Topic Modelling with Word and Document Representations Topic Modeling With TFIDF 3.mp4

04:27

488 - Topic Modelling with Word and Document Representations Topic Modeling With TFIDF 4.mp4

04:52

489 - Topic Modelling with Word and Document Representations Topic Modeling With TFIDF 5.mp4

04:40

490 - Topic Modelling with Word and Document Representations Topic Modeling With Gensim.mp4

13:26

491 - Word Embeddings LSI Word Cooccurrence Matrix.mp4

06:25

492 - Word Embeddings LSI Word Cooccurrence Matrix vs Documentterm Matrix.mp4

05:47

493 - Word Embeddings LSI Word Cooccurrence Matrix Implementation Preparing Data.mp4

05:08

494 - Word Embeddings LSI Word Cooccurrence Matrix Implementation Preparing Data 2.mp4

04:13

495 - Word Embeddings LSI Word Cooccurrence Matrix Implementation Preparing Data Getting Vocabulary.mp4

04:26

496 - Word Embeddings LSI Word Cooccurrence Matrix Implementation Final Function.mp4

11:37

497 - Word Embeddings LSI Word Cooccurrence Matrix Implementation Handling Memory Issues On Large Corp.mp4

09:19

498 - Word Embeddings LSI Word Cooccurrence Matrix Sparsity.mp4

05:19

499 - Word Embeddings LSI Word Cooccurrence Matrix Positive Point Wise Mutual Information PPMI.mp4

07:58

500 - Word Embeddings LSI PCA For Dense Embeddings.mp4

05:31

501 - Word Embeddings LSI Latent Semantic Analysis.mp4

04:25

502 - Word Embeddings LSI Latent Semantic Analysis Implementation.mp4

06:50

503 - Word Semantics Cosine Similarity.mp4

07:05

504 - Word Semantics Cosine Similarity Geting Norms Of Vectors.mp4

09:18

505 - Word Semantics Cosine Similarity Normalizing Vectors.mp4

06:36

506 - Word Semantics Cosine Similarity With More Than One Vectors.mp4

11:00

507 - Word Semantics Cosine Similarity Getting Most Similar Words In The Vocabulary.mp4

10:05

508 - Word Semantics Cosine Similarity Getting Most Similar Words In The Vocabulary Fixingbug Of D.mp4

06:23

509 - Word Semantics Cosine Similarity Word2Vec Embeddings.mp4

08:21

510 - Word Semantics Words Analogies.mp4

04:50

511 - Word Semantics Words Analogies Implemenation 1.mp4

05:55

512 - Word Semantics Words Analogies Implemenation 2.mp4

06:13

513 - Word Semantics Words Visualizations.mp4

02:37

514 - Word Semantics Words Visualizations Implementaion.mp4

04:28

515 - Word Semantics Words Visualizations Implementaion 2.mp4

06:36

516 - Word2vec Static And Dynamic Embeddings.mp4

06:17

517 - Word2vec Self Supervision.mp4

04:23

518 - Word2vec Word2Vec Algorithm Abstract.mp4

05:21

519 - Word2vec Word2Vec Why Negative Sampling.mp4

03:49

520 - Word2vec Word2Vec What Is Skip Gram.mp4

04:43

521 - Word2vec Word2Vec How To Define Probability Law.mp4

04:00

522 - Word2vec Word2Vec Sigmoid.mp4

05:21

523 - Word2vec Word2Vec Formalizing Loss Function.mp4

05:49

524 - Word2vec Word2Vec Loss Function.mp4

03:25

525 - Word2vec Word2Vec Gradient Descent Step.mp4

04:21

526 - Word2vec Word2Vec Implemenation Preparing Data.mp4

10:37

527 - Word2vec Word2Vec Implemenation Gradient Step.mp4

07:18

528 - Word2vec Word2Vec Implemenation Driver Function.mp4

13:38

529 - Need of Deep Learning for NLP Why RNNs For NLP.mp4

13:25

530 - Need of Deep Learning for NLP Pytorch Installation And Tensors Introduction.mp4

10:32

531 - Need of Deep Learning for NLP Automatic Diffrenciation Pytorch.mp4

08:26

532 - IntroductionNLP with Deep Learning DNN Why DNNs In Machine Learning.mp4

04:13

533 - IntroductionNLP with Deep Learning DNN Representational Power And Data Utilization Capacity Of DNN.mp4

07:13

534 - IntroductionNLP with Deep Learning DNN Perceptron.mp4

05:08

535 - IntroductionNLP with Deep Learning DNN Perceptron Implementation.mp4

07:26

536 - IntroductionNLP with Deep Learning DNN DNN Architecture.mp4

03:52

537 - IntroductionNLP with Deep Learning DNN DNN Forwardstep Implementation.mp4

08:21

538 - IntroductionNLP with Deep Learning DNN DNN Why Activation Function Is Require.mp4

04:47

539 - IntroductionNLP with Deep Learning DNN DNN Properties Of Activation Function.mp4

06:04

540 - IntroductionNLP with Deep Learning DNN DNN Activation Functions In Pytorch.mp4

03:49

541 - IntroductionNLP with Deep Learning DNN DNN What Is Loss Function.mp4

07:10

542 - IntroductionNLP with Deep Learning DNN DNN Loss Function In Pytorch.mp4

05:45

543 - TrainingNLP with DNN DNN Gradient Descent.mp4

05:58

544 - TrainingNLP with DNN DNN Gradient Descent Implementation.mp4

06:51

545 - TrainingNLP with DNN DNN Gradient Descent Stochastic Batch Minibatch.mp4

07:07

546 - TrainingNLP with DNN DNN Gradient Descent Summary.mp4

02:38

547 - TrainingNLP with DNN DNN Implemenation Gradient Step.mp4

04:02

548 - TrainingNLP with DNN DNN Implemenation Stochastic Gradient Descent.mp4

13:53

549 - TrainingNLP with DNN DNN Implemenation Batch Gradient Descent.mp4

06:46

550 - TrainingNLP with DNN DNN Implemenation Minibatch Gradient Descent.mp4

09:04

551 - TrainingNLP with DNN DNN Implemenation In Pytorch.mp4

15:19

552 - Hyper parametersNLP with DNN DNN Weights Initializations.mp4

04:35

553 - Hyper parametersNLP with DNN DNN Learning Rate.mp4

04:03

554 - Hyper parametersNLP with DNN DNN Batch Normalization.mp4

02:05

555 - Hyper parametersNLP with DNN DNN Batch Normalization Implementation.mp4

02:41

556 - Hyper parametersNLP with DNN DNN Optimizations.mp4

04:08

557 - Hyper parametersNLP with DNN DNN Dropout.mp4

03:58

558 - Hyper parametersNLP with DNN DNN Dropout In Pytorch.mp4

02:03

559 - Hyper parametersNLP with DNN DNN Early Stopping.mp4

03:34

560 - Hyper parametersNLP with DNN DNN Hyperparameters.mp4

03:33

561 - Hyper parametersNLP with DNN DNN Pytorch CIFAR10 Example.mp4

15:56

562 - IntroductionNLP with Deep Learning RNN What Is RNN.mp4

04:54

563 - IntroductionNLP with Deep Learning RNN Understanding RNN With A Simple Example.mp4

08:30

564 - IntroductionNLP with Deep Learning RNN RNN Applications Human Activity Recognition.mp4

02:53

565 - IntroductionNLP with Deep Learning RNN RNN Applications Image Captioning.mp4

02:37

566 - IntroductionNLP with Deep Learning RNN RNN Applications Machine Translation.mp4

15:56

567 - IntroductionNLP with Deep Learning RNN RNN Applications Speech Recognition Stock Price Prediction.mp4

04:05

568 - IntroductionNLP with Deep Learning RNN RNN Models.mp4

07:07

569 - Miniproject Language Modelling Language Modeling Next Word Prediction.mp4

03:43

570 - Miniproject Language Modelling Language Modeling Next Word Prediction Vocabulary Index.mp4

04:04

571 - Miniproject Language Modelling Language Modeling Next Word Prediction Vocabulary Index Embeddings.mp4

03:16

572 - Miniproject Language Modelling Language Modeling Next Word Prediction Rnn Architecture.mp4

04:09

573 - Miniproject Language Modelling Language Modeling Next Word Prediction Python 1.mp4

07:12

574 - Miniproject Language Modelling Language Modeling Next Word Prediction Python 2.mp4

09:02

575 - Miniproject Language Modelling Language Modeling Next Word Prediction Python 3.mp4

07:27

576 - Miniproject Language Modelling Language Modeling Next Word Prediction Python 4.mp4

09:02

577 - Miniproject Language Modelling Language Modeling Next Word Prediction Python 5.mp4

04:35

578 - Miniproject Language Modelling Language Modeling Next Word Prediction Python 6.mp4

13:34

579 - Miniproject Sentiment Classification Vocabulary Implementation.mp4

09:46

580 - Miniproject Sentiment Classification Vocabulary Implementation Helpers.mp4

05:50

581 - Miniproject Sentiment Classification Vocabulary Implementation From File.mp4

06:26

582 - Miniproject Sentiment Classification Vectorizer.mp4

05:17

583 - Miniproject Sentiment Classification RNN Setup.mp4

07:20

584 - Miniproject Sentiment Classification RNN Setup 1.mp4

21:23

585 - RNN in PyTorch RNN In Pytorch Introduction.mp4

02:04

586 - RNN in PyTorch RNN In Pytorch Embedding Layer.mp4

07:21

587 - RNN in PyTorch RNN In Pytorch Nn Rnn.mp4

08:47

588 - RNN in PyTorch RNN In Pytorch Output Shapes.mp4

04:11

589 - RNN in PyTorch RNN In Pytorch Gatedunits.mp4

03:39

590 - RNN in PyTorch RNN In Pytorch Gatedunits GRU LSTM.mp4

03:55

591 - RNN in PyTorch RNN In Pytorch Bidirectional RNN.mp4

02:44

592 - RNN in PyTorch RNN In Pytorch Bidirectional RNN Output Shapes.mp4

04:26

593 - RNN in PyTorch RNN In Pytorch Bidirectional RNN Output Shapes Seperation.mp4

04:33

594 - RNN in PyTorch RNN In Pytorch Example.mp4

09:48

595 - Advanced RNN models RNN Encoder Decoder.mp4

03:01

596 - Advanced RNN models RNN Attention.mp4

03:28

597 - Neural Machine Translation Introduction To Dataset And Packages.mp4

05:10

598 - Neural Machine Translation Implementing Language Class.mp4

05:22

599 - Neural Machine Translation Testing Language Class And Implementing Normalization.mp4

09:44

600 - Neural Machine Translation Reading Datafile.mp4

05:17

601 - Neural Machine Translation Reading Building Vocabulary.mp4

07:56

602 - Neural Machine Translation EncoderRNN.mp4

06:14

603 - Neural Machine Translation DecoderRNN.mp4

06:13

604 - Neural Machine Translation DecoderRNN Forward Step.mp4

12:08

605 - Neural Machine Translation DecoderRNN Helper Functions.mp4

04:54

606 - Neural Machine Translation Training Module.mp4

13:31

607 - Neural Machine Translation Stochastic Gradient Descent.mp4

07:12

608 - Neural Machine Translation NMT Training.mp4

05:06

609 - Neural Machine Translation NMT Evaluation.mp4

11:13

6 - Advanced Chatbots with Deep Learning Python

610 - Links for the Courses Materials and Codes.html

611 - Introduction Course and Instructor Introduction.mp4

02:16

612 - Introduction AI Sciences Introduction.mp4

01:28

613 - Introduction Course Description.mp4

03:19

614 - Fundamentals of Chatbots for Deep Learning Module Introduction.mp4

04:10

615 - Fundamentals of Chatbots for Deep Learning Conventional vs AI Chatbots.mp4

05:48

616 - Fundamentals of Chatbots for Deep Learning Geneative vs Retrievel Chatbots.mp4

04:07

617 - Fundamentals of Chatbots for Deep Learning Benifits of Deep Learning Chatbots.mp4

04:30

618 - Fundamentals of Chatbots for Deep Learning Chatbots in Medical Domain.mp4

04:35

619 - Fundamentals of Chatbots for Deep Learning Chatbots in Business.mp4

04:37

620 - Fundamentals of Chatbots for Deep Learning Chatbots in ECommerce.mp4

02:51

621 - Deep Learning Based Chatbot Architecture and Develpment Module Introduction.mp4

02:55

622 - Deep Learning Based Chatbot Architecture and Develpment Deep Learning Architect.mp4

02:18

623 - Deep Learning Based Chatbot Architecture and Develpment Encoder Decoder.mp4

01:44

624 - Deep Learning Based Chatbot Architecture and Develpment Steps Involved.mp4

01:56

625 - Deep Learning Based Chatbot Architecture and Develpment Project Overview and Packages.mp4

03:50

626 - Deep Learning Based Chatbot Architecture and Develpment Importing Libraries.mp4

05:20

627 - Deep Learning Based Chatbot Architecture and Develpment Data Prepration.mp4

06:43

628 - Deep Learning Based Chatbot Architecture and Develpment Develop Vocabulary.mp4

05:08

629 - Deep Learning Based Chatbot Architecture and Develpment Max Story and Question Length.mp4

03:46

630 - Deep Learning Based Chatbot Architecture and Develpment Tokenizer.mp4

02:58

631 - Deep Learning Based Chatbot Architecture and Develpment Separation and Sequence.mp4

05:06

632 - Deep Learning Based Chatbot Architecture and Develpment Vectorize Stories.mp4

09:36

633 - Deep Learning Based Chatbot Architecture and Develpment Vectorizing Train and Test Data.mp4

05:43

634 - Deep Learning Based Chatbot Architecture and Develpment Encoding.mp4

06:49

635 - Deep Learning Based Chatbot Architecture and Develpment Answer and Response.mp4

05:39

636 - Deep Learning Based Chatbot Architecture and Develpment Model Completion.mp4

05:02

637 - Deep Learning Based Chatbot Architecture and Develpment Predictions.mp4

04:27

7 - Recommender Systems An Applied Approach using Deep Learning

638 - Links for the Courses Materials and Codes.html

639 - Introduction Course Outline.mp4

02:22

640 - Deep Learning Foundation for Recommender Systems Module Introduction.mp4

02:36

641 - Deep Learning Foundation for Recommender Systems Overview.mp4

03:32

642 - Deep Learning Foundation for Recommender Systems Deep Learning in Recommendation Systems.mp4

03:49

643 - Deep Learning Foundation for Recommender Systems Inference After Training.mp4

03:03

644 - Deep Learning Foundation for Recommender Systems Inference Mechanism.mp4

03:09

645 - Deep Learning Foundation for Recommender Systems Embeddings and User Context.mp4

05:25

646 - Deep Learning Foundation for Recommender Systems Neutral Collaborative Filterin.mp4

03:17

647 - Deep Learning Foundation for Recommender Systems VAE Collaborative Filtering.mp4

03:09

648 - Deep Learning Foundation for Recommender Systems Strengths and Weaknesses of DL Models.mp4

03:49

649 - Deep Learning Foundation for Recommender Systems Deep Learning Quiz.mp4

00:30

650 - Deep Learning Foundation for Recommender Systems Deep Learning Quiz Solution.mp4

01:52

651 - Project Amazon Product Recommendation System Module Overview.mp4

01:56

652 - Project Amazon Product Recommendation System TensorFlow Recommenders.mp4

01:11

653 - Project Amazon Product Recommendation System Two Tower Model.mp4

02:26

654 - Project Amazon Product Recommendation System Project Overview.mp4

01:41

655 - Project Amazon Product Recommendation System Download Libraries.mp4

04:08

656 - Project Amazon Product Recommendation System Data Visualization with WordCloud.mp4

08:35

657 - Project Amazon Product Recommendation System Make Tensors from DataFrame.mp4

06:07

658 - Project Amazon Product Recommendation System Rating Our Data.mp4

06:06

659 - Project Amazon Product Recommendation System Random TrainTest Split.mp4

05:04

660 - Project Amazon Product Recommendation System Making the Model and Query Tower.mp4

08:14

661 - Project Amazon Product Recommendation System Candidate Tower and Retrieval System.mp4

05:57

662 - Project Amazon Product Recommendation System Compute Loss.mp4

03:04

663 - Project Amazon Product Recommendation System Train and Validation.mp4

10:58

664 - Project Amazon Product Recommendation System Accuracy vs Recommendations.mp4

08:01

665 - Project Amazon Product Recommendation System Making Recommendations.mp4

07:11

Description

Unlock the Secrets of Deep Learning: Dive Deep into CNNs, RNNs, NLP, Chatbots, and Recommender Systems - Deep Learning

What You'll Learn?

Hands-on Projects: Engage in practical projects spanning image analysis, language translation, chatbot creation, and recommendation systems.
Deep Learning Fundamentals: Understand the core principles of deep learning and its applications across various domains.
Convolutional Neural Networks (CNNs): Master image processing, object detection, and advanced CNN architectures like LeNet, AlexNet, and ResNet.
Recurrent Neural Networks (RNNs) and Sequence Modeling: Explore sequence processing, language understanding, and modern RNN variants such as LSTM.
Natural Language Processing (NLP) Essentials: Dive into text preprocessing, word embeddings, and deep learning applications in language understanding.
Integration and Application: Combine knowledge from different modules to develop comprehensive deep learning solutions through a capstone project.

Who is this for?

Aspiring Data Scientists: Individuals aiming to specialize in deep learning and expand their knowledge in AI applications.

Programmers and Developers: Those seeking to venture into the field of artificial intelligence and harness Python for deep learning projects.

AI Enthusiasts and Learners: Anyone passionate about understanding CNNs, RNNs, NLP, chatbots, and recommender systems within the realm of deep learning.

Students and Researchers: Those pursuing academic endeavors or conducting research in machine learning and AI-related fields.

Professionals Exploring Career Shifts: Individuals interested in transitioning or advancing their careers in artificial intelligence and deep learning.

Tech Enthusiasts: Individuals keen on exploring cutting-edge technologies and applications within the AI domain.

What You Need to Know?

Understanding Python fundamentals is recommended for implementing deep learning concepts covered in the course.

More details

Description
Welcome to the ultimate Deep Learning masterclass! This comprehensive course integrates six modules, each providing a deep dive into different aspects of Deep Learning using Python. Whether you're a beginner looking to build a strong foundation or an intermediate learner seeking to advance your skills, this course offers practical insights, theoretical knowledge, and hands-on projects to cater to your needs.Â Â

Who Should Take This Course?
Beginners interested in diving into the world of Deep Learning with Python
Intermediate learners looking to enhance their Deep Learning skills
Anyone aspiring to understand and apply Deep Learning concepts in real-world projects

Why This Course?
This course offers an all-encompassing resource that covers a wide range of Deep Learning topics, making it suitable for learners at different levels. From fundamentals to advanced concepts, you will gain a comprehensive understanding of Deep Learning using Python through practical applications.Â

What You Will Learn:
Module 1: Deep Learning Fundamentals with Python
Introduction to Deep Learning
Python basics for Deep Learning
Data preprocessing for Deep Learning algorithms
General machine learning concepts
Module 2: Convolutional Neural Networks (CNNs) in Depth
In-depth understanding of CNNs
Classical computer vision techniques
Basics of Deep Neural Networks
Architectures like LeNet, AlexNet, InceptionNet, ResNet
Transfer Learning and YOLO Case Study
Module 3: Recurrent Neural Networks (RNNs) and Sequence Modeling
Exploration of RNNs
Applications and importance of RNNs
Addressing vanishing gradients in RNNs
Modern RNNs: LSTM, Bi-Directional RNNs, Attention Models
Implementation of RNNs using TensorFlow
Module 4: Natural Language Processing (NLP) Fundamentals
Mastery of NLP
NLP foundations and significance
Text preprocessing techniques
Word embeddings: Word2Vec, GloVe, BERT
Deep Learning in NLP: Neural Networks, RNNs, and Advanced Models
Module 5: Developing Chatbots using Deep Learning
Building Chatbot systems
Deep Learning fundamentals for Chatbots
Comparison of conventional vs. Deep Learning-based Chatbots
Practical implementation of RNN-based Chatbots
Comprehensive package: Projects and advanced models
Module 6: Recommender Systems using Deep Learning
Application of Recommender Systems
Deep Learning's role in Recommender Systems
Benefits and challenges
Developing Recommender Systems with TensorFlow
Real-world project: Amazon Product Recommendation System
Final Capstone Project
Integration and application
Hands-on project: Developing a comprehensive Deep Learning solution
Final assessment and evaluation

This comprehensive course merges the essentials of Deep Learning, covering CNNs, RNNs, NLP, Chatbots, and Recommender Systems, offering a thorough understanding of Python-based implementations. Enroll now to gain expertise in various domains of Deep Learning through hands-on projects and theoretical foundations.Â Â

Keywords and Skills:
Deep Learning Mastery
Python Deep Learning Course
CNNs and RNNs Training
NLP Fundamentals Tutorial
Chatbot Development Workshop
Recommender Systems with TensorFlow
AI Course for Beginners
Hands-on Deep Learning Projects
Python Programming for AI
Comprehensive Deep Learning Curriculum
Who this course is for:
Aspiring Data Scientists: Individuals aiming to specialize in deep learning and expand their knowledge in AI applications.
Programmers and Developers: Those seeking to venture into the field of artificial intelligence and harness Python for deep learning projects.
AI Enthusiasts and Learners: Anyone passionate about understanding CNNs, RNNs, NLP, chatbots, and recommender systems within the realm of deep learning.
Students and Researchers: Those pursuing academic endeavors or conducting research in machine learning and AI-related fields.
Professionals Exploring Career Shifts: Individuals interested in transitioning or advancing their careers in artificial intelligence and deep learning.
Tech Enthusiasts: Individuals keen on exploring cutting-edge technologies and applications within the AI domain.

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We are a group of experts, PhDs and Practitioners of Artificial Intelligence, Computer Science, Machine Learning, and Statistics. Some of us work in big companies like Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM.We decided to produce a series of courses mainly dedicated to beginners and newcomers on the techniques and methods of Machine Learning, Statistics, Artificial Intelligence, and Data Science. Initially, our objective was to help only those who wish to understand these techniques more easily and to be able to start without too much theory and without a long reading. Today we also publish a more complete course on some topics for a wider audience.Our courses have had phenomenal success. Our Courses have helped more than 100,000 students to master AI and Data Science.

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Udemy

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Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.