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01 Introduction and Outline/quizzes/001 What can linear regression be used for.html
2.53KB
02 1-D Linear Regression Theory and Code/quizzes/002 R-squared.html
2.43KB
03 Multiple linear regression and polynomial regression/quizzes/003 R-squared.html
2.82KB
04 Practical machine learning issues/quizzes/004 One-hot encoding.html
2.93KB
01 Introduction and Outline/001 Introduction and Outline.mp4
6.33MB
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01 Introduction and Outline/002 What is machine learning How does linear regression play a role.mp4
8.43MB
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01 Introduction and Outline/003 Introduction to Moores Law Problem.mp4
4.41MB
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01 Introduction and Outline/004 How to Succeed in this Course.mp4
8.78MB
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02 1-D Linear Regression Theory and Code/005 Define the model in 1-D derive the solution Updated Version.mp4
19.34MB
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02 1-D Linear Regression Theory and Code/006 Define the model in 1-D derive the solution.mp4
24.66MB
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02 1-D Linear Regression Theory and Code/007 Coding the 1-D solution in Python.mp4
14.43MB
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02 1-D Linear Regression Theory and Code/008 Determine how good the model is - r-squared.mp4
11.3MB
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02 1-D Linear Regression Theory and Code/009 R-squared in code.mp4
4.5MB
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02 1-D Linear Regression Theory and Code/010 Demonstrating Moores Law in Code.mp4
17.5MB
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03 Multiple linear regression and polynomial regression/011 Define the multi-dimensional problem and derive the solution Updated Version.mp4
14.43MB
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03 Multiple linear regression and polynomial regression/012 Define the multi-dimensional problem and derive the solution.mp4
36.07MB
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03 Multiple linear regression and polynomial regression/013 How to solve multiple linear regression using only matrices.mp4
3.09MB
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03 Multiple linear regression and polynomial regression/014 Coding the multi-dimensional solution in Python.mp4
14.91MB
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03 Multiple linear regression and polynomial regression/015 Polynomial regression - extending linear regression with Python code.mp4
16.39MB
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03 Multiple linear regression and polynomial regression/016 Predicting Systolic Blood Pressure from Age and Weight.mp4
12.34MB
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04 Practical machine learning issues/017 What do all these letters mean.mp4
9.63MB
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04 Practical machine learning issues/018 Interpreting the Weights.mp4
6.04MB
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04 Practical machine learning issues/019 Generalization error train and test sets.mp4
4.38MB
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04 Practical machine learning issues/020 Generalization and Overfitting Demonstration in Code.mp4
17.25MB
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04 Practical machine learning issues/021 Categorical inputs.mp4
8.18MB
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04 Practical machine learning issues/022 Probabilistic Interpretation of Squared Error.mp4
8.13MB
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04 Practical machine learning issues/023 L2 Regularization - Theory.mp4
6.59MB
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04 Practical machine learning issues/024 L2 Regularization - Code.mp4
8.08MB
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04 Practical machine learning issues/025 The Dummy Variable Trap.mp4
6.07MB
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04 Practical machine learning issues/026 Gradient Descent Tutorial.mp4
7.7MB
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04 Practical machine learning issues/027 Gradient Descent for Linear Regression.mp4
3.5MB
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04 Practical machine learning issues/028 Bypass the Dummy Variable Trap with Gradient Descent.mp4
8.5MB
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04 Practical machine learning issues/029 L1 Regularization - Theory.mp4
4.66MB
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04 Practical machine learning issues/030 L1 Regularization - Code.mp4
8.26MB
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04 Practical machine learning issues/031 L1 vs L2 Regularization.mp4
4.8MB
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05 Conclusion and Next Steps/032 Brief overview of advanced linear regression and machine learning topics.mp4
8.13MB
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05 Conclusion and Next Steps/033 Exercises practice and how to get good at this.mp4
7.16MB
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06 Appendix/034 BONUS Where to get Udemy coupons and FREE deep learning material.mp4
4.02MB
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06 Appendix/035 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4
43.92MB
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06 Appendix/036 How to Code by Yourself part 1.mp4
24.53MB
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06 Appendix/037 How to Code by Yourself part 2.mp4
14.8MB
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[FreeTutorials.Us].txt
75B
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