Practical Transfer Learning ( Deep Learning )in Python

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Mosin hasan

5:45:40

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1. Introduction

1. Introduction and Course Outline.mp4

03:17

2.1 flower_photos-500.zip

2.2 path for poet.zip

2.3 tensorflow-for-poets-2-master.zip

2. Do you want to be poet.mp4

07:14

3.1 One More link for peots.html

3.2 Tensor flow for poets link.html

3. Becoming Poet Part 1.mp4

09:20

4. Becoming Poet Part 2.mp4

13:03

5. Becoming Poet Part 3.mp4

03:39

6. Three main motivation for Transfer Learning.mp4

04:59

7. Success of Transfer Learning - Andrew Ng.mp4

03:37

8. Transfer Learning vs Traditional ML and Deep Learning.mp4

04:48

9. Transfer Learning vs Traditional ML and Deep Learning 2.mp4

04:25

2. Understanding Transfer Learning

1. Basic Understanding of Transfer Learning.mp4

05:07

2. Technical Terms of Transfer Learning.mp4

05:49

3. What , How and When to do Transfer Learning.mp4

04:15

4. Negative Transfer Learning.mp4

02:04

5. Inductive Bias.mp4

01:28

6. Transfer Learning in Deep Learning.mp4

08:49

7. Types of Transfer Learning in Deep Learning.mp4

05:24

8. Top-1 and Top-5 Accuracy.mp4

06:10

3. Google Teachable Machine - Unlimited edge for Transfer Learning

1. Introduction to Teachable Machine.mp4

04:44

2. Mask Face Classification.mp4

03:37

3. Indian Rupee Classification.mp4

07:01

4. Audio Classification - Man in Black.mp4

06:50

5. Audio Classification - Bell and Clap.mp4

03:39

6. Pose Classification - Bad Posture.mp4

02:45

7. Pose Classification - Yoga pose.mp4

02:56

8. Yoga Pose Testing.mp4

00:36

9. Tensorflow.js Model Deployment with p5.mp4

09:10

10. More Internal Deployment.mp4

02:50

11. Labels and Confidence Detail.mp4

02:59

12. Android Deployment.mp4

07:43

4. Worth Reading Articles

1.1 Additional Resources.zip

1. Articles.html

5. Transfer Learning in Python

1. Downloaded Model Location.mp4

01:19

2. Direct Use of Model.mp4

17:44

3. Dataset Preparation for Custom Model.mp4

17:23

4. Making of Custom Model - Last Layer change.mp4

11:02

5. Fitting of Custom Model - 4 Class Model.mp4

03:03

6. Monkey Species Classification

1.1 videorecord.zip

1. Model Downloading.mp4

01:19

2.1 monkeyclassification.zip

2. Existing Models Checking.mp4

11:54

3. Data Loading -1.mp4

09:28

4. Data Loading One Hot Encoding.mp4

08:19

5. Resnet Custom Model.mp4

10:03

6. Fitting Custom Resnet Model.mp4

07:22

7. Basic CNN Model on Monkey Dataset.mp4

05:12

8. Fitting Basic Model.mp4

01:20

9. Thank you - For the Course.mp4

01:36

7. (Optional ) 4 Classes Model (Cat , dog, horse, human)

1.1 4class.zip

1. Checking against pre-trained model.mp4

17:44

2. Dataset Preparation for Custom Model.mp4

17:23

3. Custom Model.mp4

11:02

4. Fitting the Model.mp4

03:03

8. (Optional)Full Demo - DOG CAT Classifier

1.1 Cat Dog Dataset.html

1.2 train.zip

1. Data Preparation-1.mp4

16:32

2.1 full transfer learning code.docx

2. Image to Numpy Array.mp4

08:28

3. Label Encoding.mp4

04:55

4. Basic CNN Model-1.mp4

09:11

5. CNN Model-2 with Drop out and More layer.mp4

02:00

Description

Don't Be Hero - Next Frontier in Deep Learning Image Classification and Object Detection Problems solution - Keras

What You'll Learn?

Transfer Learning for Image Classification
Google Teachable Machine
Transfer Learning in Python
Deep Learning on Steroid

Who is this for?

Deep Learning Enthusiastic

Anyone who want to jump start Machine Learning

More details

Description
Don't be Hero . as It is well said..
Let;s Enroll and utilize works of Hero for our problems.
Everyone can not do research like Yann Lecun or Andrew Ng. They are focused on improving machine learning algorithms for better world.
But as an individual and for industry, we are more concern with specific application and its accuracy.

Transfer Learning is the solution for many existing problems. Transfer learning uses existing knowledge of previously learned model to new frontier.
I will demonstrate code to do Transfer Learning in Image Classification.

Knowledge gain to recognize cycle and bike can be used to recognize car.
There are various ways we can achieve transfer learning. I will discuss Pre trained model, Fine tunning and feature extraction techniques.
Once again. Let's not be Hero . and enroll in this course.
Who this course is for:
Deep Learning Enthusiastic
Anyone who want to jump start Machine Learning

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Expert in Machine Learning and Deep Learning.Certification from Coursera and Udemy on ML and Deep Learning.Counselor to Undergraduate students.Engineer with more than 14 Years of Experience.Likes to discuss and work on social issues -like Internet Addiction, Education System and Religious talks. I have written two books on C# and .NET. I have conducted more than 50 sessions on various aspects on Computer Science.

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