Complete 2022 Data Science & Machine Learning Bootcamp

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Complete 2022 Data Science & Machine Learning Bootcamp

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Complete 2022 Data Science & Machine Learning Bootcamp
01 - Introduction to the Course
001 What is Machine Learning.mp4
MP4
40.37 MB
001 What is Machine Learning_en.vtt
VTT
6.02 KB
002 What is Data Science.mp4
MP4
39.83 MB
002 What is Data Science_en.vtt
VTT
5.04 KB
003 Download the Syllabus.html
HTML
994 B
004 Top Tips for Succeeding on this Course.html
HTML
2.06 KB
005 Course Resources List.html
HTML
1.12 KB
18162714-ML-Data-Science-Syllabus.pdf
PDF
103.97 KB
external-assets-links.txt
TXT
120 B
02 - Predict Movie Box Office Revenue with Linear Regression
001 Introduction to Linear Regression & Specifying the Problem.mp4
MP4
26.51 MB
001 Introduction to Linear Regression & Specifying the Problem_en.vtt
VTT
7.58 KB
002 Gather & Clean the Data.mp4
MP4
40.86 MB
002 Gather & Clean the Data_en.vtt
VTT
12.2 KB
003 Explore & Visualise the Data with Python.mp4
MP4
105.12 MB
003 Explore & Visualise the Data with Python_en.vtt
VTT
26.99 KB
004 The Intuition behind the Linear Regression Model.mp4
MP4
12.86 MB
004 The Intuition behind the Linear Regression Model_en.vtt
VTT
9.45 KB
005 Analyse and Evaluate the Results.mp4
MP4
75.46 MB
005 Analyse and Evaluate the Results_en.vtt
VTT
19.58 KB
006 Download the Complete Notebook Here.html
HTML
242 B
007 Join the Student Community.html
HTML
715 B
008 Any Feedback on this Section.html
HTML
512 B
18175084-01-Linear-Regression-checkpoint.ipynb.zip
ZIP
37.64 KB
18175146-01-Linear-Regression-complete.ipynb.zip
ZIP
75.28 KB
9246634-cost-revenue-dirty.csv
CSV
374.68 KB
9249290-cost-revenue-clean.csv
CSV
90.82 KB
external-assets-links.txt
TXT
212 B
03 - Python Programming for Data Science and Machine Learning
001 Windows Users - Install Anaconda.mp4
MP4
32.19 MB
001 Windows Users - Install Anaconda_en.vtt
VTT
7.72 KB
002 Mac Users - Install Anaconda.mp4
MP4
39.12 MB
002 Mac Users - Install Anaconda_en.vtt
VTT
7.07 KB
003 Does LSD Make You Better at Maths.mp4
MP4
15.63 MB
003 Does LSD Make You Better at Maths_en.vtt
VTT
6.42 KB
004 Download the 12 Rules to Learn to Code.html
HTML
1.12 KB
005 [Python] - Variables and Types.mp4
MP4
47.55 MB
005 [Python] - Variables and Types_en.vtt
VTT
14.49 KB
006 [Python] - Lists and Arrays.mp4
MP4
35.09 MB
006 [Python] - Lists and Arrays_en.vtt
VTT
10.55 KB
007 [Python & Pandas] - Dataframes and Series.mp4
MP4
101.4 MB
007 [Python & Pandas] - Dataframes and Series_en.vtt
VTT
24.43 KB
008 [Python] - Module Imports.mp4
MP4
186.86 MB
008 [Python] - Module Imports_en.vtt
VTT
31.45 KB
009 [Python] - Functions - Part 1 Defining and Calling Functions.mp4
MP4
27.38 MB
009 [Python] - Functions - Part 1 Defining and Calling Functions_en.vtt
VTT
9.15 KB
010 [Python] - Functions - Part 2 Arguments & Parameters.mp4
MP4
99.44 MB
010 [Python] - Functions - Part 2 Arguments & Parameters_en.vtt
VTT
18.18 KB
011 [Python] - Functions - Part 3 Results & Return Values.mp4
MP4
54.13 MB
011 [Python] - Functions - Part 3 Results & Return Values_en.vtt
VTT
14.46 KB
012 [Python] - Objects - Understanding Attributes and Methods.mp4
MP4
125.35 MB
012 [Python] - Objects - Understanding Attributes and Methods_en.vtt
VTT
25.93 KB
013 How to Make Sense of Python Documentation for Data Visualisation.mp4
MP4
138.12 MB
013 How to Make Sense of Python Documentation for Data Visualisation_en.vtt
VTT
23.06 KB
014 Working with Python Objects to Analyse Data.mp4
MP4
135.45 MB
014 Working with Python Objects to Analyse Data_en.vtt
VTT
23.55 KB
015 [Python] - Tips, Code Style and Naming Conventions.mp4
MP4
67.18 MB
015 [Python] - Tips, Code Style and Naming Conventions_en.vtt
VTT
14.66 KB
016 Download the Complete Notebook Here.html
HTML
242 B
017 Any Feedback on this Section.html
HTML
513 B
18179882-02-Python-Intro.ipynb.zip
ZIP
36.44 KB
18204473-12-Rules-to-Learn-to-Code.pdf
PDF
2.25 MB
18877814-lsd-math-score-data.csv
CSV
155 B
GetFreeCourses.Co.url
URL
116 B
external-assets-links.txt
TXT
83 B
04 - Introduction to Optimisation and the Gradient Descent Algorithm
001 What's Coming Up.mp4
MP4
12.92 MB
001 What's Coming Up_en.vtt
VTT
3.36 KB
002 How a Machine Learns.mp4
MP4
10.47 MB
002 How a Machine Learns_en.vtt
VTT
6.32 KB
003 Introduction to Cost Functions.mp4
MP4
39.02 MB
003 Introduction to Cost Functions_en.vtt
VTT
8.19 KB
004 LaTeX Markdown and Generating Data with Numpy.mp4
MP4
47.01 MB
004 LaTeX Markdown and Generating Data with Numpy_en.vtt
VTT
14.82 KB
005 Understanding the Power Rule & Creating Charts with Subplots.mp4
MP4
59.49 MB
005 Understanding the Power Rule & Creating Charts with Subplots_en.vtt
VTT
15.59 KB
006 [Python] - Loops and the Gradient Descent Algorithm.mp4
MP4
92.92 MB
006 [Python] - Loops and the Gradient Descent Algorithm_en.vtt
VTT
37.63 KB
007 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4
MP4
229.5 MB
007 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1)_en.vtt
VTT
37.23 KB
008 [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4
MP4
145.22 MB
008 [Python] - Tuples and the Pitfalls of Optimisation (Part 2)_en.vtt
VTT
29.03 KB
009 Understanding the Learning Rate.mp4
MP4
190.14 MB
009 Understanding the Learning Rate_en.vtt
VTT
32.56 KB
010 How to Create 3-Dimensional Charts.mp4
MP4
152.02 MB
010 How to Create 3-Dimensional Charts_en.vtt
VTT
22.61 KB
011 Understanding Partial Derivatives and How to use SymPy.mp4
MP4
102.67 MB
011 Understanding Partial Derivatives and How to use SymPy_en.vtt
VTT
17.62 KB
012 Implementing Batch Gradient Descent with SymPy.mp4
MP4
65.49 MB
012 Implementing Batch Gradient Descent with SymPy_en.vtt
VTT
11.26 KB
013 [Python] - Loops and Performance Considerations.mp4
MP4
106.59 MB
013 [Python] - Loops and Performance Considerations_en.vtt
VTT
15.67 KB
014 Reshaping and Slicing N-Dimensional Arrays.mp4
MP4
95.11 MB
014 Reshaping and Slicing N-Dimensional Arrays_en.vtt
VTT
19.97 KB
015 Concatenating Numpy Arrays.mp4
MP4
32.48 MB
015 Concatenating Numpy Arrays_en.vtt
VTT
7.8 KB
016 Introduction to the Mean Squared Error (MSE).mp4
MP4
43.24 MB
016 Introduction to the Mean Squared Error (MSE)_en.vtt
VTT
11.02 KB
017 Transposing and Reshaping Arrays.mp4
MP4
58.02 MB
017 Transposing and Reshaping Arrays_en.vtt
VTT
11.69 KB
018 Implementing a MSE Cost Function.mp4
MP4
54.55 MB
018 Implementing a MSE Cost Function_en.vtt
VTT
11.74 KB
019 Understanding Nested Loops and Plotting the MSE Function (Part 1).mp4
MP4
48.88 MB
019 Understanding Nested Loops and Plotting the MSE Function (Part 1)_en.vtt
VTT
12.12 KB
020 Plotting the Mean Squared Error (MSE) on a Surface (Part 2).mp4
MP4
96.91 MB
020 Plotting the Mean Squared Error (MSE) on a Surface (Part 2)_en.vtt
VTT
14.98 KB
021 Running Gradient Descent with a MSE Cost Function.mp4
MP4
74.32 MB
021 Running Gradient Descent with a MSE Cost Function_en.vtt
VTT
19.24 KB
022 Visualising the Optimisation on a 3D Surface.mp4
MP4
35.61 MB
022 Visualising the Optimisation on a 3D Surface_en.vtt
VTT
9.35 KB
023 Download the Complete Notebook Here.html
HTML
242 B
024 Any Feedback on this Section.html
HTML
520 B
18179908-03-Gradient-Descent.ipynb.zip
ZIP
1.14 MB
external-assets-links.txt
TXT
83 B
05 - Predict House Prices with Multivariable Linear Regression
001 Defining the Problem.mp4
MP4
30.02 MB
001 Defining the Problem_en.vtt
VTT
5.61 KB
002 Gathering the Boston House Price Data.mp4
MP4
47.58 MB
002 Gathering the Boston House Price Data_en.vtt
VTT
7.55 KB
003 Clean and Explore the Data (Part 1) Understand the Nature of the Dataset.mp4
MP4
56.73 MB
003 Clean and Explore the Data (Part 1) Understand the Nature of the Dataset_en.vtt
VTT
13.66 KB
004 Clean and Explore the Data (Part 2) Find Missing Values.mp4
MP4
107.48 MB
004 Clean and Explore the Data (Part 2) Find Missing Values_en.vtt
VTT
16.27 KB
005 Visualising Data (Part 1) Historams, Distributions & Outliers.mp4
MP4
42.62 MB
005 Visualising Data (Part 1) Historams, Distributions & Outliers_en.vtt
VTT
12.39 KB
006 Visualising Data (Part 2) Seaborn and Probability Density Functions.mp4
MP4
37.6 MB
006 Visualising Data (Part 2) Seaborn and Probability Density Functions_en.vtt
VTT
7.84 KB
007 Working with Index Data, Pandas Series, and Dummy Variables.mp4
MP4
103.76 MB
007 Working with Index Data, Pandas Series, and Dummy Variables_en.vtt
VTT
17.97 KB
008 Understanding Descriptive Statistics the Mean vs the Median.mp4
MP4
41.03 MB
008 Understanding Descriptive Statistics the Mean vs the Median_en.vtt
VTT
10.64 KB
009 Introduction to Correlation Understanding Strength & Direction.mp4
MP4
12.92 MB
009 Introduction to Correlation Understanding Strength & Direction_en.vtt
VTT
7.37 KB
010 Calculating Correlations and the Problem posed by Multicollinearity.mp4
MP4
82.51 MB
010 Calculating Correlations and the Problem posed by Multicollinearity_en.vtt
VTT
15.48 KB
011 Visualising Correlations with a Heatmap.mp4
MP4
108.43 MB
011 Visualising Correlations with a Heatmap_en.vtt
VTT
21.22 KB
012 Techniques to Style Scatter Plots.mp4
MP4
83.87 MB
012 Techniques to Style Scatter Plots_en.vtt
VTT
18.04 KB
013 A Note for the Next Lesson.html
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476 B
014 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.mp4
MP4
175.24 MB
014 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques_en.vtt
VTT
25 KB
015 Understanding Multivariable Regression.mp4
MP4
31.51 MB
015 Understanding Multivariable Regression_en.vtt
VTT
6.57 KB
016 How to Shuffle and Split Training & Testing Data.mp4
MP4
45.09 MB
016 How to Shuffle and Split Training & Testing Data_en.vtt
VTT
9.99 KB
017 Running a Multivariable Regression.mp4
MP4
40.2 MB
017 Running a Multivariable Regression_en.vtt
VTT
8.53 KB
018 How to Calculate the Model Fit with R-Squared.mp4
MP4
21.48 MB
018 How to Calculate the Model Fit with R-Squared_en.vtt
VTT
3.84 KB
019 Introduction to Model Evaluation.mp4
MP4
7.34 MB
019 Introduction to Model Evaluation_en.vtt
VTT
3.31 KB
020 Improving the Model by Transforming the Data.mp4
MP4
81.41 MB
020 Improving the Model by Transforming the Data_en.vtt
VTT
18.78 KB
021 How to Interpret Coefficients using p-Values and Statistical Significance.mp4
MP4
49.02 MB
021 How to Interpret Coefficients using p-Values and Statistical Significance_en.vtt
VTT
9.48 KB
022 Understanding VIF & Testing for Multicollinearity.mp4
MP4
105.42 MB
022 Understanding VIF & Testing for Multicollinearity_en.vtt
VTT
22.29 KB
023 Model Simplification & Baysian Information Criterion.mp4
MP4
119.72 MB
023 Model Simplification & Baysian Information Criterion_en.vtt
VTT
20.18 KB
024 How to Analyse and Plot Regression Residuals.mp4
MP4
28.05 MB
024 How to Analyse and Plot Regression Residuals_en.vtt
VTT
12.85 KB
025 Residual Analysis (Part 1) Predicted vs Actual Values.mp4
MP4
81.48 MB
025 Residual Analysis (Part 1) Predicted vs Actual Values_en.vtt
VTT
15.74 KB
026 Residual Analysis (Part 2) Graphing and Comparing Regression Residuals.mp4
MP4
99.19 MB
026 Residual Analysis (Part 2) Graphing and Comparing Regression Residuals_en.vtt
VTT
19.68 KB
027 Making Predictions (Part 1) MSE & R-Squared.mp4
MP4
126.58 MB
027 Making Predictions (Part 1) MSE & R-Squared_en.vtt
VTT
20.51 KB
028 Making Predictions (Part 2) Standard Deviation, RMSE, and Prediction Intervals.mp4
MP4
63.72 MB
028 Making Predictions (Part 2) Standard Deviation, RMSE, and Prediction Intervals_en.vtt
VTT
12.88 KB
029 Build a Valuation Tool (Part 1) Working with Pandas Series & Numpy ndarrays.mp4
MP4
102.57 MB
029 Build a Valuation Tool (Part 1) Working with Pandas Series & Numpy ndarrays_en.vtt
VTT
17.87 KB
030 [Python] - Conditional Statements - Build a Valuation Tool (Part 2).mp4
MP4
90.12 MB
030 [Python] - Conditional Statements - Build a Valuation Tool (Part 2)_en.vtt
VTT
18.44 KB
031 Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module.mp4
MP4
200.93 MB
031 Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module_en.vtt
VTT
24.52 KB
032 Download the Complete Notebook Here.html
HTML
242 B
033 Any Feedback on this Section.html
HTML
512 B
18179918-04-Multivariable-Regression.ipynb.zip
ZIP
3.54 MB
18179928-04-Valuation-Tool.ipynb.zip
ZIP
2.93 KB
18905386-boston-valuation.py
PY
3.05 KB
external-assets-links.txt
TXT
83 B
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1
001 How to Translate a Business Problem into a Machine Learning Problem.mp4
MP4
31.01 MB
001 How to Translate a Business Problem into a Machine Learning Problem_en.vtt
VTT
8.46 KB
002 Gathering Email Data and Working with Archives & Text Editors.mp4
MP4
95.99 MB
002 Gathering Email Data and Working with Archives & Text Editors_en.vtt
VTT
12.26 KB
003 How to Add the Lesson Resources to the Project.mp4
MP4
18.95 MB
003 How to Add the Lesson Resources to the Project_en.vtt
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4.24 KB
004 The Naive Bayes Algorithm and the Decision Boundary for a Classifier.mp4
MP4
29.41 MB
004 The Naive Bayes Algorithm and the Decision Boundary for a Classifier_en.vtt
VTT
5.36 KB
005 Basic Probability.mp4
MP4
9.4 MB
005 Basic Probability_en.vtt
VTT
4.62 KB
006 Joint & Conditional Probability.mp4
MP4
88.31 MB
006 Joint & Conditional Probability_en.vtt
VTT
17.25 KB
007 Bayes Theorem.mp4
MP4
51.07 MB
007 Bayes Theorem_en.vtt
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13.19 KB
008 Reading Files (Part 1) Absolute Paths and Relative Paths.mp4
MP4
39.54 MB
008 Reading Files (Part 1) Absolute Paths and Relative Paths_en.vtt
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10.29 KB
009 Reading Files (Part 2) Stream Objects and Email Structure.mp4
MP4
87.76 MB
009 Reading Files (Part 2) Stream Objects and Email Structure_en.vtt
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12.75 KB
010 Extracting the Text in the Email Body.mp4
MP4
30.49 MB
010 Extracting the Text in the Email Body_en.vtt
VTT
5.19 KB
011 [Python] - Generator Functions & the yield Keyword.mp4
MP4
104.22 MB
011 [Python] - Generator Functions & the yield Keyword_en.vtt
VTT
19.48 KB
012 Create a Pandas DataFrame of Email Bodies.mp4
MP4
37.37 MB
012 Create a Pandas DataFrame of Email Bodies_en.vtt
VTT
6.24 KB
013 Cleaning Data (Part 1) Check for Empty Emails & Null Entries.mp4
MP4
90.33 MB
013 Cleaning Data (Part 1) Check for Empty Emails & Null Entries_en.vtt
VTT
15.52 KB
014 Cleaning Data (Part 2) Working with a DataFrame Index.mp4
MP4
46.5 MB
014 Cleaning Data (Part 2) Working with a DataFrame Index_en.vtt
VTT
7.95 KB
015 Saving a JSON File with Pandas.mp4
MP4
43.41 MB
015 Saving a JSON File with Pandas_en.vtt
VTT
6.09 KB
016 Data Visualisation (Part 1) Pie Charts.mp4
MP4
70.09 MB
016 Data Visualisation (Part 1) Pie Charts_en.vtt
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14.02 KB
017 Data Visualisation (Part 2) Donut Charts.mp4
MP4
40.95 MB
017 Data Visualisation (Part 2) Donut Charts_en.vtt
VTT
8.31 KB
018 Introduction to Natural Language Processing (NLP).mp4
MP4
37.45 MB
018 Introduction to Natural Language Processing (NLP)_en.vtt
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7.22 KB
019 Tokenizing, Removing Stop Words and the Python Set Data Structure.mp4
MP4
92.53 MB
019 Tokenizing, Removing Stop Words and the Python Set Data Structure_en.vtt
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16.58 KB
020 Word Stemming & Removing Punctuation.mp4
MP4
46.64 MB
020 Word Stemming & Removing Punctuation_en.vtt
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9.39 KB
021 Removing HTML tags with BeautifulSoup.mp4
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86.57 MB
021 Removing HTML tags with BeautifulSoup_en.vtt
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9.73 KB
022 Creating a Function for Text Processing.mp4
MP4
26.36 MB
022 Creating a Function for Text Processing_en.vtt
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7.21 KB
023 A Note for the Next Lesson.html
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476 B
024 Advanced Subsetting on DataFrames the apply() Function.mp4
MP4
55.26 MB
024 Advanced Subsetting on DataFrames the apply() Function_en.vtt
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11.79 KB
025 [Python] - Logical Operators to Create Subsets and Indices.mp4
MP4
57.42 MB
025 [Python] - Logical Operators to Create Subsets and Indices_en.vtt
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13.4 KB
026 Word Clouds & How to install Additional Python Packages.mp4
MP4
50.04 MB
026 Word Clouds & How to install Additional Python Packages_en.vtt
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10.49 KB
027 Creating your First Word Cloud.mp4
MP4
45.54 MB
027 Creating your First Word Cloud_en.vtt
VTT
12.01 KB
028 Styling the Word Cloud with a Mask.mp4
MP4
105.94 MB
028 Styling the Word Cloud with a Mask_en.vtt
VTT
14.5 KB
029 Solving the Hamlet Challenge.mp4
MP4
46.79 MB
029 Solving the Hamlet Challenge_en.vtt
VTT
5.21 KB
030 Styling Word Clouds with Custom Fonts.mp4
MP4
99.44 MB
030 Styling Word Clouds with Custom Fonts_en.vtt
VTT
12.88 KB
031 Create the Vocabulary for the Spam Classifier.mp4
MP4
70.09 MB
031 Create the Vocabulary for the Spam Classifier_en.vtt
VTT
15.4 KB
032 Coding Challenge Check for Membership in a Collection.mp4
MP4
14.85 MB
032 Coding Challenge Check for Membership in a Collection_en.vtt
VTT
5.31 KB
033 Coding Challenge Find the Longest Email.mp4
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41.1 MB
033 Coding Challenge Find the Longest Email_en.vtt
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6.55 KB
034 Sparse Matrix (Part 1) Split the Training and Testing Data.mp4
MP4
58.08 MB
034 Sparse Matrix (Part 1) Split the Training and Testing Data_en.vtt
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13.17 KB
035 Sparse Matrix (Part 2) Data Munging with Nested Loops.mp4
MP4
91.56 MB
035 Sparse Matrix (Part 2) Data Munging with Nested Loops_en.vtt
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19.39 KB
036 Sparse Matrix (Part 3) Using groupby() and Saving .txt Files.mp4
MP4
61.3 MB
036 Sparse Matrix (Part 3) Using groupby() and Saving .txt Files_en.vtt
VTT
10.46 KB
037 Coding Challenge Solution Preparing the Test Data.mp4
MP4
18.88 MB
037 Coding Challenge Solution Preparing the Test Data_en.vtt
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3.93 KB
038 Checkpoint Understanding the Data.mp4
MP4
74.56 MB
038 Checkpoint Understanding the Data_en.vtt
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11.87 KB
039 Download the Complete Notebook Here.html
HTML
242 B
040 Any Feedback on this Section.html
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519 B
18179924-06-Bayes-Classifier-Pre-Processing.ipynb.zip
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978.02 KB
18190724-SpamData.zip
ZIP
21.28 MB
GetFreeCourses.Co.url
URL
116 B
external-assets-links.txt
TXT
83 B
07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2
001 Setting up the Notebook and Understanding Delimiters in a Dataset.mp4
MP4
53.98 MB
001 Setting up the Notebook and Understanding Delimiters in a Dataset_en.vtt
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9.8 KB
002 Create a Full Matrix.mp4
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104.85 MB
002 Create a Full Matrix_en.vtt
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19.11 KB
003 Count the Tokens to Train the Naive Bayes Model.mp4
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63.64 MB
003 Count the Tokens to Train the Naive Bayes Model_en.vtt
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16.19 KB
004 Sum the Tokens across the Spam and Ham Subsets.mp4
MP4
24.37 MB
004 Sum the Tokens across the Spam and Ham Subsets_en.vtt
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6.89 KB
005 Calculate the Token Probabilities and Save the Trained Model.mp4
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35.29 MB
005 Calculate the Token Probabilities and Save the Trained Model_en.vtt
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8.26 KB
006 Coding Challenge Prepare the Test Data.mp4
MP4
28.62 MB
006 Coding Challenge Prepare the Test Data_en.vtt
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4.57 KB
007 Download the Complete Notebook Here.html
HTML
242 B
008 Any Feedback on this Section.html
HTML
527 B
18180042-07-Bayes-Classifier-Training.ipynb.zip
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5.82 KB
18190704-SpamData.zip
ZIP
22.31 MB
external-assets-links.txt
TXT
83 B
08 - Test and Evaluate a Naive Bayes Classifier Part 3
001 Set up the Testing Notebook.mp4
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19.97 MB
001 Set up the Testing Notebook_en.vtt
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3.34 KB
002 Joint Conditional Probability (Part 1) Dot Product.mp4
MP4
47.03 MB
002 Joint Conditional Probability (Part 1) Dot Product_en.vtt
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11.06 KB
003 Joint Conditional Probablity (Part 2) Priors.mp4
MP4
45.8 MB
003 Joint Conditional Probablity (Part 2) Priors_en.vtt
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9.53 KB
004 Making Predictions Comparing Joint Probabilities.mp4
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37.12 MB
004 Making Predictions Comparing Joint Probabilities_en.vtt
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8.78 KB
005 The Accuracy Metric.mp4
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28.66 MB
005 The Accuracy Metric_en.vtt
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6.68 KB
006 Visualising the Decision Boundary.mp4
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149.45 MB
006 Visualising the Decision Boundary_en.vtt
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30.3 KB
007 False Positive vs False Negatives.mp4
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41.39 MB
007 False Positive vs False Negatives_en.vtt
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11.47 KB
008 The Recall Metric.mp4
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18.41 MB
008 The Recall Metric_en.vtt
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5.76 KB
009 The Precision Metric.mp4
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34.47 MB
009 The Precision Metric_en.vtt
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8.42 KB
010 The F-score or F1 Metric.mp4
MP4
16.46 MB
010 The F-score or F1 Metric_en.vtt
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4.47 KB
011 A Naive Bayes Implementation using SciKit Learn.mp4
MP4
145.69 MB
011 A Naive Bayes Implementation using SciKit Learn_en.vtt
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29.27 KB
012 Download the Complete Notebook Here.html
HTML
242 B
013 Any Feedback on this Section.html
HTML
509 B
18180294-07-Bayes-Classifier-Testing-Inference-Evaluation.ipynb.zip
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243.05 KB
18180296-08-Naive-Bayes-with-scikit-learn.ipynb.zip
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13.26 KB
18190700-SpamData.zip
ZIP
22.83 MB
external-assets-links.txt
TXT
83 B
09 - Introduction to Neural Networks and How to Use Pre-Trained Models
001 The Human Brain and the Inspiration for Artificial Neural Networks.mp4
MP4
32.71 MB
001 The Human Brain and the Inspiration for Artificial Neural Networks_en.vtt
VTT
9.96 KB
002 Layers, Feature Generation and Learning.mp4
MP4
124.35 MB
002 Layers, Feature Generation and Learning_en.vtt
VTT
24.61 KB
003 Costs and Disadvantages of Neural Networks.mp4
MP4
76.56 MB
003 Costs and Disadvantages of Neural Networks_en.vtt
VTT
16.96 KB
004 Preprocessing Image Data and How RGB Works.mp4
MP4
69.24 MB
004 Preprocessing Image Data and How RGB Works_en.vtt
VTT
14.37 KB
005 Importing Keras Models and the Tensorflow Graph.mp4
MP4
49.24 MB
005 Importing Keras Models and the Tensorflow Graph_en.vtt
VTT
10.32 KB
006 Making Predictions using InceptionResNet.mp4
MP4
103.2 MB
006 Making Predictions using InceptionResNet_en.vtt
VTT
17.08 KB
007 Coding Challenge Solution Using other Keras Models.mp4
MP4
81.98 MB
007 Coding Challenge Solution Using other Keras Models_en.vtt
VTT
11.83 KB
008 Download the Complete Notebook Here.html
HTML
264 B
009 Any Feedback on this Section.html
HTML
526 B
18180490-09-Neural-Nets-Pretrained-Image-Classification.ipynb.zip
ZIP
571.83 KB
18188466-TF-Keras-Classification-Images.zip
ZIP
501.1 KB
GetFreeCourses.Co.url
URL
116 B
external-assets-links.txt
TXT
83 B
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow
001 Solving a Business Problem with Image Classification.mp4
MP4
19.47 MB
001 Solving a Business Problem with Image Classification_en.vtt
VTT
4.49 KB
002 Installing Tensorflow and Keras for Jupyter.mp4
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31.92 MB
002 Installing Tensorflow and Keras for Jupyter_en.vtt
VTT
5.9 KB
003 Gathering the CIFAR 10 Dataset.mp4
MP4
20.6 MB
003 Gathering the CIFAR 10 Dataset_en.vtt
VTT
5.48 KB
004 Exploring the CIFAR Data.mp4
MP4
81.16 MB
004 Exploring the CIFAR Data_en.vtt
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16.11 KB
005 Pre-processing Scaling Inputs and Creating a Validation Dataset.mp4
MP4
61.32 MB
005 Pre-processing Scaling Inputs and Creating a Validation Dataset_en.vtt
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17.8 KB
006 Compiling a Keras Model and Understanding the Cross Entropy Loss Function.mp4
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76.04 MB
006 Compiling a Keras Model and Understanding the Cross Entropy Loss Function_en.vtt
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16.58 KB
007 Interacting with the Operating System and the Python Try-Catch Block.mp4
MP4
45.79 MB
007 Interacting with the Operating System and the Python Try-Catch Block_en.vtt
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21.52 KB
008 Fit a Keras Model and Use Tensorboard to Visualise Learning and Spot Problems.mp4
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76.55 MB
008 Fit a Keras Model and Use Tensorboard to Visualise Learning and Spot Problems_en.vtt
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12.76 KB
009 Use Regularisation to Prevent Overfitting Early Stopping & Dropout Techniques.mp4
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152.54 MB
009 Use Regularisation to Prevent Overfitting Early Stopping & Dropout Techniques_en.vtt
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25.08 KB
010 Use the Model to Make Predictions.mp4
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173.85 MB
010 Use the Model to Make Predictions_en.vtt
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30.18 KB
011 Model Evaluation and the Confusion Matrix.mp4
MP4
40.05 MB
011 Model Evaluation and the Confusion Matrix_en.vtt
VTT
9.6 KB
012 Model Evaluation and the Confusion Matrix.mp4
MP4
193.26 MB
012 Model Evaluation and the Confusion Matrix_en.vtt
VTT
35.46 KB
013 Download the Complete Notebook Here.html
HTML
242 B
014 Any Feedback on this Section.html
HTML
521 B
18187728-10-Neural-Nets-Keras-CIFAR10-Classification.ipynb.zip
ZIP
120.11 KB
external-assets-links.txt
TXT
83 B
11 - Use Tensorflow to Classify Handwritten Digits
001 What's coming up.mp4
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5.23 MB
001 What's coming up_en.vtt
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2.32 KB
002 Getting the Data and Loading it into Numpy Arrays.mp4
MP4
39.66 MB
002 Getting the Data and Loading it into Numpy Arrays_en.vtt
VTT
8.19 KB
003 Data Exploration and Understanding the Structure of the Input Data.mp4
MP4
20.6 MB
003 Data Exploration and Understanding the Structure of the Input Data_en.vtt
VTT
5.73 KB
004 Data Preprocessing One-Hot Encoding and Creating the Validation Dataset.mp4
MP4
49.34 MB
004 Data Preprocessing One-Hot Encoding and Creating the Validation Dataset_en.vtt
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11.48 KB
005 What is a Tensor.mp4
MP4
37.85 MB
005 What is a Tensor_en.vtt
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8.18 KB
006 Creating Tensors and Setting up the Neural Network Architecture.mp4
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110.62 MB
006 Creating Tensors and Setting up the Neural Network Architecture_en.vtt
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26.2 KB
007 Defining the Cross Entropy Loss Function, the Optimizer and the Metrics.mp4
MP4
49.63 MB
007 Defining the Cross Entropy Loss Function, the Optimizer and the Metrics_en.vtt
VTT
12.68 KB
008 TensorFlow Sessions and Batching Data.mp4
MP4
73.63 MB
008 TensorFlow Sessions and Batching Data_en.vtt
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18.27 KB
009 Tensorboard Summaries and the Filewriter.mp4
MP4
98.73 MB
009 Tensorboard Summaries and the Filewriter_en.vtt
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21.25 KB
010 Understanding the Tensorflow Graph Nodes and Edges.mp4
MP4
89.48 MB
010 Understanding the Tensorflow Graph Nodes and Edges_en.vtt
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18.52 KB
011 Name Scoping and Image Visualisation in Tensorboard.mp4
MP4
66.81 MB
011 Name Scoping and Image Visualisation in Tensorboard_en.vtt
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23.85 KB
012 Different Model Architectures Experimenting with Dropout.mp4
MP4
173.82 MB
012 Different Model Architectures Experimenting with Dropout_en.vtt
VTT
27.03 KB
013 Prediction and Model Evaluation.mp4
MP4
87.34 MB
013 Prediction and Model Evaluation_en.vtt
VTT
16.75 KB
014 Download the Complete Notebook Here.html
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242 B
015 Any Feedback on this Section.html
HTML
499 B
18187740-11-Neural-Networks-TF-Handwriting-Recognition.ipynb.zip
ZIP
6.6 KB
18194656-MNIST.zip
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14.77 MB
external-assets-links.txt
TXT
83 B
12 - Serving a Tensorflow Model through a Website
001 What you'll make.mp4
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35.52 MB
001 What you'll make_en.vtt
VTT
8.73 KB
002 Saving Tensorflow Models.mp4
MP4
103.67 MB
002 Saving Tensorflow Models_en.vtt
VTT
19 KB
003 Loading a SavedModel.mp4
MP4
85.1 MB
003 Loading a SavedModel_en.vtt
VTT
23.15 KB
004 Converting a Model to Tensorflow.js.mp4
MP4
93.61 MB
004 Converting a Model to Tensorflow.js_en.vtt
VTT
18.79 KB
005 Introducing the Website Project and Tooling.mp4
MP4
68.79 MB
005 Introducing the Website Project and Tooling_en.vtt
VTT
15.68 KB
006 HTML and CSS Styling.mp4
MP4
136.76 MB
006 HTML and CSS Styling_en.vtt
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33.85 KB
007 Loading a Tensorflow.js Model and Starting your own Server.mp4
MP4
175.41 MB
007 Loading a Tensorflow.js Model and Starting your own Server_en.vtt
VTT
33.67 KB
008 Adding a Favicon.mp4
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24.34 MB
008 Adding a Favicon_en.vtt
VTT
6.5 KB
009 Styling an HTML Canvas.mp4
MP4
172.69 MB
009 Styling an HTML Canvas_en.vtt
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35.37 KB
010 Drawing on an HTML Canvas.mp4
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159.28 MB
010 Drawing on an HTML Canvas_en.vtt
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33.21 KB
011 Data Pre-Processing for Tensorflow.js.mp4
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25.56 MB
011 Data Pre-Processing for Tensorflow.js_en.vtt
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10.73 KB
012 Introduction to OpenCV.mp4
MP4
133.24 MB
012 Introduction to OpenCV_en.vtt
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34.43 KB
013 Resizing and Adding Padding to Images.mp4
MP4
147.83 MB
013 Resizing and Adding Padding to Images_en.vtt
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24.19 KB
014 Calculating the Centre of Mass and Shifting the Image.mp4
MP4
210.44 MB
014 Calculating the Centre of Mass and Shifting the Image_en.vtt
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32.1 KB
015 Making a Prediction from a Digit drawn on the HTML Canvas.mp4
MP4
98.46 MB
015 Making a Prediction from a Digit drawn on the HTML Canvas_en.vtt
VTT
15.37 KB
016 Adding the Game Logic.mp4
MP4
158.22 MB
016 Adding the Game Logic_en.vtt
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33.58 KB
017 Publish and Share your Website!.mp4
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33.31 MB
017 Publish and Share your Website!_en.vtt
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8.19 KB
018 Any Feedback on this Section.html
HTML
500 B
21028850-11-Neural-Networks-TF-Handwriting-Recognition.ipynb.zip
ZIP
6.39 KB
21028876-MNIST-Model-Load-Files.zip
ZIP
2.84 MB
21028894-TFJS.zip
ZIP
1.54 MB
21028914-math-garden-stub.zip
ZIP
44.03 KB
21028926-math-garden-stub-complete.zip
ZIP
4.09 MB
21028932-math-garden-stub-12.12-checkpoint.zip
ZIP
4.09 MB
21028968-12-TF-SavedModel-Export-Completed.ipynb.zip
ZIP
6.13 KB
21028978-x-test0-ylabel7.txt
TXT
4.59 KB
21028982-x-test1-ylabel2.txt
TXT
4.59 KB
21028988-x-test2-ylabel1.txt
TXT
4.59 KB
GetFreeCourses.Co.url
URL
116 B
13 - Next Steps
001 Where next.html
HTML
3.9 KB
002 What Modules Do You Want to See.html
HTML
431 B
003 Stay in Touch!.html
HTML
1.05 KB
Download Paid Udemy Courses For Free.url
URL
116 B
GetFreeCourses.Co.url
URL
116 B

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