Python Fundamentals
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01 Introduction to Python Fundamentals LiveLessons Part 1.mp4
13:25
02 Lesson overview.mp4
01:49
03 Getting the code.mp4
00:49
04 Structure of the examples folder.mp4
04:26
05 Installing Anaconda.mp4
03:19
06 Updating Anaconda.mp4
05:18
07 Package managers.mp4
02:29
08 Installing jupyter matplotlib.mp4
01:28
09 Twitter developer account.mp4
01:57
10 Getting your questions answered.mp4
01:49
11 Lesson overview.mp4
03:40
12 Using IPython Interactive Mode as a Calculator.mp4
15:49
13 Executing a Python Program Using the IPython Interpreter.mp4
09:01
14 Writing and Executing Code in a Jupyter Notebook.mp4
24:11
15 Lesson overview.mp4
03:14
16 Variables and Assignment Statements.mp4
13:14
17 Self Check.mp4
02:21
18 Arithmetic.mp4
12:13
19 Self Check.mp4
02:43
20 Function print and an Intro to Single and Double Quoted Strings.mp4
11:09
21 Self Check.mp4
01:50
22 Triple Quoted Strings.mp4
07:33
23 Self Check.mp4
03:18
24 Getting Input from the User.mp4
10:53
25 Self Check.mp4
03:18
26 Decision Making The if Statement and Comparison Operators.mp4
20:23
27 Self Check.mp4
02:07
28 Objects and Dynamic Typing.mp4
07:58
29 Self Check.mp4
01:10
30 Intro to Data Science Basic Descriptive Statistics.mp4
11:47
31 Self Check.mp4
01:59
32 Lesson overview.mp4
02:48
33 if Statement.mp4
07:57
34 Self Check.mp4
02:16
35 ifelse and ifelifelse Statements.mp4
10:51
36 Self Check.mp4
01:50
37 while Statement.mp4
02:25
38 Self Check.mp4
01:17
39 for Statement; Iterables, Lists and Iterators; Built in range Function.mp4
11:28
40 Self Check.mp4
02:12
41 Augmented Assignments.mp4
02:06
42 Self Check.mp4
00:48
43 Sequence Controlled Iteration.mp4
06:19
44 Self Check.mp4
01:39
45 Sentinel Controlled Iteration.mp4
08:11
46 Built In Function range A Deeper Look.mp4
03:38
47 Self Check.mp4
02:25
48 Using Type Decimal for Monetary Amounts.mp4
18:23
49 Self Check.mp4
02:17
50 break and continue Statements.mp4
02:28
51 Boolean Operators and, or and not.mp4
07:45
52 Self Check.mp4
02:37
53 Intro to Data Science Measures of Central Tendency, Mean, Median and Mode.mp4
11:02
54 Self Check.mp4
03:49
55 Lesson overview.mp4
03:31
56 Defining Functions.mp4
15:45
57 Self Check.mp4
01:47
58 Functions with Multiple Parameters.mp4
09:34
59 Self Check.mp4
01:49
60 Random Number Generation.mp4
18:05
61 Self Check.mp4
02:09
62 Case Study A Game of Chance.mp4
15:52
63 Self Check.mp4
02:16
64 math Module Functions.mp4
03:19
65 Default Parameter Values.mp4
03:21
66 Keyword Arguments.mp4
05:35
67 Arbitrary Argument Lists.mp4
04:53
68 Self Check.mp4
02:57
69 Methods Functions That Belong to Objects.mp4
04:52
70 Scope Rules.mp4
11:26
71 import A Deeper Look.mp4
05:38
72 Self Check.mp4
01:08
73 Passing Arguments to Functions A Deeper Look.mp4
08:28
74 Self Check.mp4
01:20
75 Functional Style Programming.mp4
04:49
76 Intro to Data Science Measures of Dispersion.mp4
10:02
PythonFundamentalsPart1Code.zip
001 Introduction to Python Fundamentals Part 2.mp4
07:53
002 Lesson overview.mp4
05:43
003 Lists.mp4
17:44
004 Self Check.mp4
03:40
005 Tuples.mp4
12:55
006 Self Check.mp4
02:06
007 Unpacking Sequences.mp4
11:30
008 Creating a primitive bar chart.mp4
04:58
009 Self Check.mp4
04:07
010 Sequence Slicing Part 1 Getting a Subset of a Sequence.mp4
08:32
011 Sequence Slicing Part 2 Modifying a List.mp4
06:01
012 Self Check.mp4
04:44
013 del Statement.mp4
03:21
014 Self Check.mp4
02:03
015 Passing Lists to Functions.mp4
05:02
016 Sorting Lists.mp4
06:20
017 Self Check.mp4
02:11
018 Searching Sequences.mp4
09:22
019 Self Check.mp4
01:30
020 Other List Methods.mp4
11:32
021 Self Check.mp4
02:45
022 Simulating Stacks with Lists.mp4
02:01
023 List Comprehensions.mp4
06:50
024 Self Check.mp4
02:47
025 Generator Expressions.mp4
05:54
026 Self Check.mp4
01:51
027 Filter, Map and Reduce.mp4
16:32
028 Self Check.mp4
05:30
029 Other Sequence Processing Functions.mp4
08:51
030 Self Check.mp4
03:58
031 Two Dimensional Lists.mp4
06:37
032 Self Check.mp4
02:44
033 Intro to Data Science Simulation and Static Visualizations.mp4
02:49
034 Sample Graphs for 600, 60,000 and 6,000,000 Die Rolls.mp4
06:01
035 Visualizing Die Roll Frequencies and Percentages Part 1.mp4
10:24
036 Visualizing Die Roll Frequencies and Percentages Part 2.mp4
11:10
037 Visualizing Die Roll Frequencies and Percentages Part 3.mp4
11:20
038 Visualizing Die Roll Frequencies and Percentages Part 4.mp4
07:22
039 Lesson overview.mp4
04:29
040 Dictionaries.mp4
01:35
041 Creating a Dictionary.mp4
04:56
042 Self Check.mp4
01:16
043 Iterating through a Dictionary.mp4
03:30
044 Basic Dictionary Operarations.mp4
08:09
045 Self Check.mp4
01:27
046 Dictionary Methods keys and values.mp4
07:11
047 Self Check.mp4
01:45
048 Dictionary Comparisons.mp4
02:38
049 Example Dictionary of Student Grades.mp4
04:28
050 Example Word Counts.mp4
07:48
051 Python Standard Library Module collections.mp4
04:52
052 Self Check.mp4
02:24
053 Dictionary Method update.mp4
04:39
054 Dictionary Comprehensions.mp4
04:43
055 Self Check.mp4
01:33
056 Sets.mp4
07:25
057 Self Check.mp4
01:54
058 Comparing Sets.mp4
07:20
059 Self Check.mp4
02:28
060 Mathematical Set Operations.mp4
06:40
061 Self Check.mp4
02:24
062 Mutable Set Operators and Methods.mp4
06:11
063 Set Comprehensions.mp4
01:41
064 Intro to Data Science Dynamic Visualizations How Dynamic Visualization Works.mp4
09:32
065 Intro to Data Science Dynamic Visualizations Implementing Dynamic Visualization, Part 1.mp4
17:37
066 Lesson overview.mp4
04:56
067 Creating arrays from Existing Data.mp4
03:23
068 Self Check.mp4
02:50
069 array Attributes.mp4
08:31
070 Self Check.mp4
00:57
071 Filling arrays with Specific Values.mp4
02:32
072 Creating arrays from Ranges.mp4
05:57
073 Self Check.mp4
01:37
074 List vs. array Performance Introducing %timeit.mp4
10:10
075 Self Check.mp4
02:05
076 array Operators.mp4
07:35
077 Self Check.mp4
01:02
078 NumPy Calculation Methods.mp4
06:02
079 Self Check.mp4
02:38
080 Universal Functions.mp4
05:43
081 Self Check.mp4
00:54
082 Indexing and Slicing.mp4
05:58
083 Self Check.mp4
02:49
084 Views Shallow Copies.mp4
05:31
085 Deep Copies.mp4
02:06
086 Reshaping and Transposing reshape vs. resize.mp4
02:14
087 Reshaping and Transposing flatten vs. ravel.mp4
03:23
088 Reshaping and Transposing Transposing Rows and Columns.mp4
02:04
089 Reshaping and Transposing Horizontal and Vertical Stacking.mp4
02:49
090 Self Check.mp4
01:21
091 Intro to Data Science pandas Series and DataFrames.mp4
03:57
092 Intro to Data Science pandas Series and DataFrames pandas Series Part 1.mp4
08:11
093 Intro to Data Science pandas Series and DataFrames pandas Series Part 2.mp4
08:40
094 Self Check.mp4
04:12
095 Intro to Data Science pandas Series and DataFrames Creating DataFrames and Customizing Indices.mp4
05:34
096 Intro to Data Science pandas Series and DataFrames Accessing a DataFrames Columns.mp4
01:48
097 Intro to Data Science pandas Series and DataFrames Selecting Rows via the loc and iloc Attributes.mp4
03:13
098 Intro to Data Science pandas Series and DataFrames Selecting Rows via Slices and Lists with the loc and iloc Attributes.mp4
03:03
099 Intro to Data Science pandas Series and DataFrames Selecting Subsets of the Rows and Columns.mp4
02:27
100 Intro to Data Science pandas Series and DataFrames Boolean Indexing.mp4
03:52
101 Intro to Data Science pandas Series and DataFrames Accessing a Specific DataFrame Cell by Row and Column.mp4
03:36
102 Intro to Data Science pandas Series and DataFrames Descriptive Statistics.mp4
04:08
103 Intro to Data Science pandas Series and DataFrames Transposing the DataFrame with the T Attribute.mp4
02:59
104 Intro to Data Science pandas Series and DataFrames Sorting by Indices.mp4
02:49
105 Intro to Data Science pandas Series and DataFrames Sorting by Column Values.mp4
06:55
106 Self Check.mp4
03:58
PythonFundamentalsPart2Code.zip
001 Introduction to Python Fundamentals Part 3.mp4
07:10
002 Lesson overview.mp4
01:53
003 Formatting Strings Presentation Types.mp4
04:23
004 Self Check.mp4
00:34
005 Formatting Strings Field Widths and Alignment.mp4
04:45
006 Self Check.mp4
01:06
007 Formatting Strings Numeric Formatting.mp4
02:51
008 Self Check.mp4
01:37
009 Formatting Strings Strings format Method.mp4
03:34
010 Self Check.mp4
03:03
011 Concatenating and Repeating Strings.mp4
01:51
012 Self Check.mp4
01:38
013 Stripping Whitespace from Strings.mp4
01:27
014 Self Check.mp4
01:03
015 Changing Character Case.mp4
00:47
016 Self Check.mp4
00:35
017 Comparison Operators for Strings.mp4
01:52
018 Searching for Substrings.mp4
05:07
019 Self Check.mp4
01:16
020 Replacing Substrings.mp4
00:49
021 Self Check.mp4
00:39
022 Splitting and Joining Strings.mp4
06:53
023 Self Check.mp4
03:50
024 Characters and Character Testing Methods.mp4
02:08
025 Raw Strings.mp4
02:28
026 Introduction to Regular Expressions.mp4
01:26
027 re Module and Function fullmatch Part 1 Matching Literal Characters.mp4
02:29
028 re Module and Function fullmatch Part 2 Metacharacters, Character Classes and Quantifiers.mp4
04:49
029 re Module and Function fullmatch Part 3 Custom Character Classes.mp4
03:40
030 re Module and Function fullmatch Part 1 Quantifiers.mp4
04:53
031 Self Check.mp4
02:17
032 Replacing Substrings and Splitting Strings.mp4
03:44
033 Self Check.mp4
02:10
034 Other Search Functions; Accessing Matches Function search Finding the First Match Anywhere in a String.mp4
03:17
035 Other Search Functions; Accessing Matches Ignoring Case with the Optional flags Keyword Argument.mp4
01:05
036 Other Search Functions; Accessing Matches Metacharacters that Restrict Matches to the Beginning or End of a String.mp4
01:45
037 Other Search Functions; Accessing Matches Functions findall and finditer Finding All Matches in a String.mp4
02:16
038 Other Search Functions; Accessing Matches Capturing Substrings in a Match.mp4
04:12
039 Self Check.mp4
02:18
040 Intro to Data Science Pandas, Regular Expressions and Data Munging Part 1 Introduction.mp4
04:20
041 Intro to Data Science Pandas, Regular Expressions and Data Munging Part 3 Data Validation.mp4
04:45
042 Intro to Data Science Pandas, Regular Expressions and Data Munging Part 4 Reformatting Your Data.mp4
07:18
043 Self Check.mp4
03:09
044 Lesson overview.mp4
03:36
045 Files.mp4
01:13
046 Text File Processing Writing to a Text File Introducing the with Statement.mp4
06:03
047 Self Check.mp4
01:41
048 Text File Processing Reading Data from a Text File.mp4
05:25
049 Self Check.mp4
02:05
050 Updating Text Files.mp4
06:24
051 Self Check.mp4
03:28
052 Serialization with JSON JSON Data Format.mp4
02:55
053 Serialization with JSON Serializing an Object to JSON.mp4
03:53
054 Serialization with JSON Deserializing a JSON Object into Python.mp4
02:02
055 Serialization with JSON Displaying JSON Text.mp4
03:34
056 Self Check.mp4
02:52
057 File Open Modes.mp4
02:46
058 Handling Exceptions.mp4
01:23
059 Division by Zero and Invalid Input.mp4
02:23
060 try Statements.mp4
06:51
061 Self Check.mp4
02:04
062 finally Clause.mp4
07:16
063 Self Check.mp4
01:53
064 Explicitly Raising an Exception.mp4
01:32
065 Stack Unwinding and Tracebacks.mp4
04:15
066 Intro to Data Science Working with CSV Files Python Standard Library Module csv.mp4
07:49
067 Self Check.mp4
02:09
068 Intro to Data Science Working with CSV Files Reading CSV Files into Pandas DataFrames.mp4
04:39
069 Intro to Data Science Working with CSV Files Reading the Titanic Disaster Dataset.mp4
05:40
070 Intro to Data Science Working with CSV Files Simple Data Analysis with the Titanic Disaster Dataset.mp4
04:13
071 Intro to Data Science Working with CSV Files Passenger Age Histogram.mp4
03:14
PythonFundamentalsPart3Code.zip
001 Introduction to Python Fundamentals Part 4.mp4
06:40
002 Lesson overview.mp4
05:27
003 Custom Class Account Test Driving Class Account.mp4
06:16
004 Custom Class Account Account Class Definition.mp4
12:16
005 Self Check.mp4
04:50
006 Controlling Access to Attributes.mp4
03:30
007 Properties for Data Access Test Driving Class Time.mp4
06:04
008 Properties for Data Access Class Time Definition.mp4
16:57
009 Self Check.mp4
04:35
010 Properties for Data Access Class Time Definition Notes.mp4
02:10
011 Simulating Private Attributes.mp4
05:59
012 Case Study Card Shuffling and Dealing Simulation Test Driving Classes Card and DeckOfCards.mp4
04:23
013 Case Study Card Shuffling and Dealing Simulation Class Card and an Introduction to Class Attributes.mp4
09:30
014 Case Study Card Shuffling and Dealing Simulation Class DeckOfCards.mp4
07:17
015 Case Study Card Shuffling and Dealing Simulation Displaying Card Images with Matplotlib.mp4
14:15
016 Self Check.mp4
03:33
017 Inheritance Base Classes and Subclasses.mp4
05:41
018 Building an Inheritance Hierarchy and Introducing Polymorphism Base Class CommissionEmployee.mp4
08:36
019 Building an Inheritance Hierarchy and Introducing Polymorphism Sublass SalariedCommissionEmployee.mp4
10:02
020 Building an Inheritance Hierarchy and Introducing Polymorphism Processing CommissionEmployees and SalariedCommissionEmployees Polymorphically.mp4
06:00
021 Duck Typing and Polymorphism.mp4
05:05
022 Operator Overloading.mp4
03:47
023 Test Driving Class Complex.mp4
05:51
024 Class Complex Definition.mp4
06:21
025 Self Check.mp4
03:58
026 Named Tuples.mp4
07:08
027 A Brief Intro to Python 3.7s New Data Classes.mp4
01:29
028 A Brief Intro to Python 3.7s New Data Classes Creating a Card Data Class.mp4
08:52
029 A Brief Intro to Python 3.7s New Data Classes Using the Card Data Class.mp4
04:55
030 Self Check.mp4
02:10
031 A Brief Intro to Python 3.7s New Data Classes Advantages Over Named Tuples and Traditional Classes.mp4
04:11
032 Unit Testing with Docstrings and doctest.mp4
15:42
033 Self Check.mp4
02:54
034 Namespaces and Scopes.mp4
12:35
035 Intro to Data Science Time Series and Simple Linear Regression Introduction.mp4
09:15
036 Intro to Data Science Time Series and Simple Linear Regression Components of the Simple Linear Regression Calculation.mp4
04:41
037 Intro to Data Science Time Series and Simple Linear Regression Loading the Average High Temperatures into a DataFrame.mp4
02:50
038 Intro to Data Science Time Series and Simple Linear Regression Cleaning the Data.mp4
03:46
039 Intro to Data Science Time Series and Simple Linear Regression Calculating Basic Descriptive Statistics for the Dataset.mp4
01:27
040 Intro to Data Science Time Series and Simple Linear Regression Forecasting Future January Average High Temperatures.mp4
04:59
041 Intro to Data Science Time Series and Simple Linear Regression Plotting the Average High Temperatures and a Regression Line.mp4
06:01
042 Lesson overview.mp4
03:48
043 Introduction.mp4
04:16
044 TextBlob.mp4
07:50
045 Create a TextBlob.mp4
03:02
046 Tokenizing Text into Sentences and Words.mp4
02:01
047 Parts of Speech Tagging.mp4
06:34
048 Extracting Noun Phrases.mp4
02:41
049 Sentiment Analysis with TextBlobs Default Sentiment Analyzer.mp4
02:57
050 Sentiment Analysis with the NaiveBayesAnalyzer.mp4
05:10
051 Language Detection and Translation.mp4
03:56
052 Inflection Pluralization and Singularization.mp4
03:54
053 Spell Checking and Correction.mp4
03:29
054 Normalization Stemming and Lemmatization.mp4
02:01
055 Word Frequencies.mp4
04:31
056 Getting Definitions, Synonyms and Antonyms from WordNet.mp4
07:36
057 Deleting Stop Word.mp4
04:51
058 n grams.mp4
04:09
059 Visualizing Word Frequencies with Pandas.mp4
13:15
060 Visualizing Word Frequencies with Word Clouds.mp4
09:04
061 Readability Assessment with Textatistic.mp4
04:38
062 Named Entity Recognition with spaCy.mp4
07:19
063 Similarity Detection with spaCy.mp4
09:23
064 Lesson overview.mp4
03:10
065 Introduction.mp4
04:16
066 Overview of the Twitter APIs.mp4
11:53
067 Creating a Twitter Developer Account.mp4
02:04
068 Getting Twitter Credentials Creating an App.mp4
07:14
069 Whats in a Tweet.mp4
08:57
070 Tweepy.mp4
02:26
071 Authenticating with Twitter Via Tweepy.mp4
05:46
072 Getting Information About a Twitter Account.mp4
10:30
073 Self Check.mp4
01:12
074 Introduction to Tweepy Cursors Getting an Accounts Followers and Friends.mp4
02:18
075 Determining an Accounts Followers.mp4
06:52
076 Self Check.mp4
02:14
077 Determining Whom an Account Follows.mp4
03:10
078 Getting a Users Recent Tweets.mp4
02:43
079 Self Check.mp4
01:00
080 Searching Recent Tweets.mp4
09:20
081 Self Check.mp4
01:02
082 Spotting Trends Twitter Trends API.mp4
00:59
083 Places with Trending Topics.mp4
04:19
084 Getting a List of Trending Topics.mp4
07:57
085 Self Check.mp4
02:23
086 Create a Word Cloud from Trending Topics.mp4
05:05
087 Self Check.mp4
02:23
088 Cleaning Preprocessing Tweets for Analysis.mp4
06:44
089 Twitter Streaming API.mp4
01:41
090 Creating a Subclass of StreamListener.mp4
12:01
091 Initiating Stream Processing.mp4
12:58
092 Twitter Restrictions Note.mp4
01:29
093 Tweet Sentiment Analysis.mp4
17:34
094 Geocoding and Mapping.mp4
06:54
095 Getting and Mapping the Tweets.mp4
22:17
096 Utility Functions in tweetutilities.py and Class LocationListener.mp4
10:21
097 Lesson overview.mp4
02:22
098 Introduction to Watson.mp4
05:32
099 IBM Cloud Account and Cloud Console.mp4
03:29
100 Watson Services Watson Assistant Demo.mp4
04:01
101 Watson Services Visual Recognition.mp4
05:11
102 Watson Services Speech to Text.mp4
03:57
103 Watson Services Text to Speech.mp4
02:50
104 Watson Services Language Translator.mp4
02:32
105 Watson Services Natural Language Understanding.mp4
04:02
106 Watson Services Personality Insights.mp4
03:28
107 Additional Services and Tools.mp4
05:07
108 Watson Developer Cloud Python SDK.mp4
03:38
109 Case Study Travelers Companion Translation App.mp4
01:42
110 Before You run the App.mp4
01:15
111 Before You run the App Registering for the Speech to Text Service.mp4
04:32
112 Before You run the App Registering for the Text to Speech Service.mp4
02:21
113 Before You run the App Registering for the Language Translator Service.mp4
01:19
114 Test Driving the App.mp4
08:31
115 SimpleLanguageTranslator.py Script Walkthrough.mp4
01:39
116 SimpleLanguageTranslator.py Script Walkthrough Importing Watson SDK Classes from the ibm watson Module.mp4
02:27
117 SimpleLanguageTranslator.py Script Walkthrough Other Imported Modules.mp4
01:30
118 SimpleLanguageTranslator.py Script Walkthrough Main Program Function run translator.mp4
07:06
119 SimpleLanguageTranslator.py Script Walkthrough Function speech to text.mp4
08:14
120 SimpleLanguageTranslator.py Script Walkthrough Function translate.mp4
04:44
121 SimpleLanguageTranslator.py Script Walkthrough Function text to speech.mp4
02:34
122 SimpleLanguageTranslator.py Script Walkthrough Function record audio.mp4
06:06
123 SimpleLanguageTranslator.py Script Walkthrough Function play audio.mp4
01:19
124 Watson Resources.mp4
03:36
PythonFundamentalsPart4Code.zip
001 Lesson overview.mp4
05:58
002 Introduction to Machine Learning.mp4
16:11
003 Case Study Classification with k Nearest Neighbors and the Digits Dataset, Part 1.mp4
07:40
004 k Nearest Neighbors Algorithm.mp4
03:18
005 k Nearest Neighbors Algorithm Hyperparameters and Hyperparameter Tuning.mp4
02:24
006 Loading the Dataset.mp4
01:47
007 Loading the Dataset Displaying the Description.mp4
03:55
008 Loading the Dataset Checking the Sample and Target Sizes.mp4
03:26
009 Loading the Dataset A Sample Digit Image.mp4
02:20
010 Loading the Dataset Preparing the Data for Use with Scikit Learn.mp4
02:55
011 Visualizing the Data.mp4
07:05
012 Splitting the Data for Training and Testing.mp4
07:10
013 Creating the Model.mp4
02:04
014 Training the Model.mp4
04:30
015 Predicting Digit Classes.mp4
04:51
016 Case Study Classification with k Nearest Neighbors and the Digits Dataset, Part 2.mp4
00:48
017 Metrics for Model Accuracy Estimator Method score.mp4
01:22
018 Metrics for Model Accuracy Confusion Matrix.mp4
06:27
019 Metrics for Model Accuracy Classification Report.mp4
04:24
020 Metrics for Model Accuracy Visualizing the Confusion Matrix.mp4
05:32
021 K Fold Cross Validation.mp4
07:02
022 Running Multiple Models to Find the Best One.mp4
07:00
023 Hyperparameter Tuning.mp4
05:22
024 Case Study Time Series and Simple Linear Regression.mp4
03:12
025 Loading the Average High Temperatures into a DataFrame.mp4
03:47
026 Splitting the Data for Training and Testing.mp4
05:38
027 Training the Model.mp4
03:58
028 Testing the Model.mp4
01:48
029 Predicting Future Temperatures and Estimating Past Temperatures.mp4
02:13
030 Visualizing the Dataset with the Regression Line.mp4
05:29
031 Overfitting Underfitting.mp4
01:41
032 Case Study Multiple Linear Regression with the California Housing Dataset.mp4
01:42
033 Loading the Dataset.mp4
06:55
034 Exploring the Data with Pandas.mp4
06:54
035 Visualizing the Features.mp4
13:28
036 Splitting the Data for Training and Testing.mp4
01:22
037 Training the Model.mp4
04:27
038 Testing the Model.mp4
01:40
039 Visualizing the Expected vs. Predicted Prices.mp4
06:14
040 Regression Model Metrics.mp4
03:19
041 Choosing the Best Model.mp4
06:04
042 Case Study Unsupervised Machine Learning, Part 1 Dimensionality Reduction.mp4
05:19
043 Loading the Digits Dataset.mp4
01:15
044 Creating a TSNE Estimator for Dimensionality Reduction.mp4
03:18
045 Transforming the Digits Datasets Features into Two Dimensions.mp4
02:43
046 Visualizing the Reduced Data.mp4
05:06
047 Visualizing the Reduced Data with Different Colors for Each Digit.mp4
05:08
048 Visualizing the Reduced Data in 3D.mp4
05:07
049 Case Study Unsupervised Machine Learning, Part 2 k Means Clustering.mp4
03:18
050 Loading the Iris Dataset.mp4
03:09
051 Exploring the Iris Dataset Descriptive Statistics with Pandas.mp4
06:04
052 Visualizing the Dataset with a Seaborn pairplot.mp4
08:52
053 Using a KMeans Estimator.mp4
05:19
054 Dimensionality Reduction with Principal Component Analysis.mp4
10:21
055 Choosing the Best Clustering Estimator.mp4
08:06
056 Lesson overview.mp4
02:30
057 Introduction.mp4
07:14
058 Deep Learning Applications.mp4
03:00
059 Deep Learning Demos.mp4
02:02
060 Keras Resources.mp4
01:38
061 Keras Built In Datasets.mp4
02:00
062 Custom Anaconda Environments.mp4
08:16
063 Neural Networks.mp4
06:44
064 Tensors.mp4
04:26
065 Convolutional Neural Networks for Vision; Multi Classification with the MNIST Dataset.mp4
02:50
066 Reproducibility in Keras and Deep Learning.mp4
01:18
067 Basic Keras Neural Network.mp4
03:29
068 Loading the MNIST Dataset.mp4
07:14
069 Data Exploration.mp4
01:30
070 Visualizing Digits.mp4
07:32
071 Reshaping the Image Data.mp4
05:25
072 Normalizing the Image Data.mp4
02:44
073 One Hot Encoding Converting the Labels From Integers to Categorical Data.mp4
05:12
074 Creating the Neural Network.mp4
01:22
075 Adding Layers to the Network.mp4
02:05
076 Convolution.mp4
07:42
077 Adding a Conv2D Convolution Layer to Our Model.mp4
04:50
078 Dimensionality of the First Convolution Layer, Output.mp4
01:50
079 Overfitting.mp4
03:03
080 Adding a Pooling Layer.mp4
04:39
081 Adding Another Convolutional Layer and Pooling Layer.mp4
03:14
082 Flattening the Results to One Dimension with a Keras Flatten Layer.mp4
01:40
083 Adding a Dense Layer to Reduce the Number of Features.mp4
02:09
084 Adding Another Dense Layer to Produce the Final Output.mp4
01:29
085 Printing the Models Summary.mp4
04:11
086 Visualizing a Model, Structure.mp4
03:37
087 Compiling the Model.mp4
03:00
088 Training and Evaluating the Model.mp4
08:04
089 Evaluating the Model on Unseen Data.mp4
02:12
090 Making Predictions.mp4
02:11
091 Locating the Incorrect Predictions.mp4
03:39
092 Visualizing Incorrect Predictions.mp4
04:14
093 Displaying the Probabilities for Several Incorrect Predictions.mp4
04:20
094 Saving and Loading a Model.mp4
02:25
095 Visualizing Neural Network Training with TensorBoard.mp4
21:40
096 ConvnetJS Browser Based Deep Learning Training and Visualization.mp4
04:53
097 Recurrent Neural Networks for Sequences; Sentiment Analysis with the IMDb Dataset.mp4
05:39
098 Loading the IMDb Movie Reviews Dataset.mp4
05:35
099 Data Exploration.mp4
02:47
100 Movie Review Encodings and Decoding a Review.mp4
10:04
101 Data Preparation.mp4
05:37
102 Creating the Neural Network.mp4
00:41
103 Adding an Embedding Layer.mp4
03:56
104 Adding an LSTM Layer.mp4
03:22
105 Adding a Dense Output Layer.mp4
00:43
106 Compiling the Model and Displaying the Summary.mp4
02:12
107 Training and Evaluating the Model (1 of 2).mp4
04:29
108 Training and Evaluating the Model (2 of 2).mp4
02:18
109 Tuning Deep Learning Models.mp4
03:32
110 Lesson overview.mp4
04:00
111 Introduction Databases.mp4
03:18
112 Introduction Apache Hadoop and Apache Spark.mp4
03:35
113 Introduction Internet of Things.mp4
01:36
114 Introduction Experience Cloud and Desktop Big Data Software.mp4
03:06
115 Introduction Big Data Sources.mp4
01:09
116 Relational Databases and Structured Query Language (SQL).mp4
03:27
117 A books Database.mp4
12:26
118 SELECT Queries.mp4
01:16
119 WHERE Clause.mp4
03:02
120 ORDER BY Clause.mp4
02:26
121 Merging Data from Multiple Tables INNER JOIN.mp4
01:42
122 INSERT INTO Statement.mp4
02:20
123 UPDATE Statement.mp4
01:20
124 DELETE FROM Statement.mp4
02:02
125 NoSQL and NewSQL Big Data Databases A Brief Tour.mp4
03:49
126 NoSQL Key Value Databases.mp4
01:26
127 NoSQL Document Databases.mp4
01:34
128 NoSQL Columnar Databases.mp4
02:33
129 NoSQL Graph Databases.mp4
02:05
130 NewSQL Databases.mp4
03:45
131 Case Study A MongoDB JSON Document Database.mp4
03:21
132 Creating the MongoDB Atlas Cluster.mp4
08:36
133 Streaming Tweets into MongoDB.mp4
24:08
134 Hadoop.mp4
00:51
135 Hadoop Overview.mp4
06:47
136 Summarizing Word Lengths in Romeo and Juliet via MapReduce.mp4
02:31
137 Creating an Apache Hadoop Cluster in Microsoft Azure HDInsight Part 1.mp4
03:45
138 Creating an Apache Hadoop Cluster in Microsoft Azure HDInsight Part 2.mp4
10:07
139 Hadoop Streaming.mp4
02:40
140 Implementing the Mapper.mp4
05:05
141 Implementing the Reducer.mp4
03:19
142 Preparing to Run the MapReduce Example.mp4
06:47
143 Running the MapReduce Job.mp4
10:55
144 Spark Overview.mp4
05:58
145 Docker and the Jupyter Docker Stacks.mp4
14:15
146 Word Count with Spark.mp4
16:59
147 Spark Word Count on Microsoft Azure.mp4
18:21
148 Spark Streaming Counting Twitter Hashtags Using the pysparknotebook Docker Stack.mp4
05:27
149 Streaming Tweets to a Socket.mp4
11:16
150 Summarizing Tweet Hashtags; Introducing Spark SQL.mp4
20:48
151 Internet of Things and Dashboards.mp4
01:03
152 Publish and Subscribe.mp4
00:46
153 Visualizing a PubNub Sample Live Stream with a Freeboard Dashboard.mp4
11:10
154 Simulating an Internet Connected Thermostat in Python and Creating a Dashbboard in Freeboard.io.mp4
14:20
155 Creating a Python PubNub Subscriber.mp4
11:04
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View courses LiveLessonsPearson's video training library is an indispensable learning tool for today's competitive job market. Having essential technology training and certifications can open doors for career advancement and life enrichment. We take learning personally. We've published hundreds of up-to-date videos on wide variety of key topics for Professionals and IT Certification candidates. Now you can learn from renowned industry experts from anywhere in the world, without leaving home.
- language english
- Training sessions 532
- duration 44:47:51
- Release Date 2023/11/04
