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Udemy Deep Learning Prerequisites Linear Regression in Python

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Tutorials

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Udemy Deep Learning Prerequisites Linear Regression in Python

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English

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1.1 GB

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Files:

1. Introduction and Outline.mp4 42.7 MB
1. Introduction and Outline.srt 10.8 KB
2. How to Succeed in this Course.mp4 43.8 MB
2. How to Succeed in this Course.srt 8.3 KB
3. Statistics vs. Machine Learning.mp4 55.5 MB
3. Statistics vs. Machine Learning.srt 14.7 KB
[Tutorialsplanet.NET].url 128 bytes
1. What is machine learning How does linear regression play a role.mp4 8.4 MB
1. What is machine learning How does linear regression play a role.srt 5.8 KB
10. Demonstrating Moore's Law in Code.mp4 17.5 MB
10. Demonstrating Moore's Law in Code.srt 6.9 KB
11. Moore's Law Derivation.mp4 20.2 MB
11. Moore's Law Derivation.srt 7.6 KB
12. R-squared Quiz 1.mp4 2.8 MB
12. R-squared Quiz 1.srt 2.2 KB
13. Suggestion Box.mp4 16.1 MB
13. Suggestion Box.srt 4.7 KB
2. What can linear regression be used for.html 150 bytes
3. Define the model in 1-D, derive the solution (Updated Version).mp4 19.4 MB
3. Define the model in 1-D, derive the solution (Updated Version).srt 16.5 KB
4. Define the model in 1-D, derive the solution.mp4 24.7 MB
4. Define the model in 1-D, derive the solution.srt 11.1 KB
5. Coding the 1-D solution in Python.mp4 14.4 MB
5. Coding the 1-D solution in Python.srt 5.6 KB
6. Exercise Theory vs. Code.mp4 1.0 MB
6. Exercise Theory vs. Code.srt 1.6 KB
7. Determine how good the model is - r-squared.mp4 11.3 MB
7. Determine how good the model is - r-squared.srt 4.7 KB
8. R-squared in code.mp4 4.5 MB
8. R-squared in code.srt 1.7 KB
9. Introduction to Moore's Law Problem.mp4 4.4 MB
9. Introduction to Moore's Law Problem.srt 3.7 KB
1. Define the multi-dimensional problem and derive the solution (Updated Version).mp4 14.4 MB
1. Define the multi-dimensional problem and derive the solution (Updated Version).srt 11.7 KB
2. Define the multi-dimensional problem and derive the solution.mp4 36.1 MB
2. Define the multi-dimensional problem and derive the solution.srt 12.9 KB
3. How to solve multiple linear regression using only matrices.mp4 3.1 MB
3. How to solve multiple linear regression using only matrices.srt 2.0 KB
4. Coding the multi-dimensional solution in Python.mp4 14.9 MB
4. Coding the multi-dimensional solution in Python.srt 5.2 KB
5. Polynomial regression - extending linear regression (with Python code).mp4 16.4 MB
5. Polynomial regression - extending linear regression (with Python code).srt 4.9 KB
6. Predicting Systolic Blood Pressure from Age and Weight.mp4 12.3 MB
6. Predicting Systolic Blood Pressure from Age and Weight.srt 5.5 KB
7. R-squared Quiz 2.mp4 3.5 MB
7. R-squared Quiz 2.srt 2.7 KB
1. What do all these letters mean.mp4 9.6 MB
1. What do all these letters mean.srt 8.0 KB
10. The Dummy Variable Trap.mp4 6.1 MB
10. The Dummy Variable Trap.srt 5.5 KB
11. Gradient Descent Tutorial.mp4 22.8 MB
11. Gradient Descent Tutorial.srt 5.5 KB
12. Gradient Descent for Linear Regression.mp4 3.5 MB
12. Gradient Descent for Linear Regression.srt 3.1 KB
13. Bypass the Dummy Variable Trap with Gradient Descent.mp4 8.5 MB
13. Bypass the Dummy Variable Trap with Gradient Descent.srt 3.6 KB
14. L1 Regularization - Theory.mp4 4.7 MB
14. L1 Regularization - Theory.srt 4.1 KB
15. L1 Regularization - Code.mp4 8.3 MB
15. L1 Regularization - Code.srt 3.5 KB
16. L1 vs L2 Regularization.mp4 4.8 MB
16. L1 vs L2 Regularization.srt 4.3 KB
17. Why Divide by Square Root of D.mp4 23.5 MB
17. Why Divide by Square Root of D.srt 8.7 KB
2. Interpreting the Weights.mp4 14.2 MB
2. Interpreting the Weights.srt 4.3 KB
3. Generalization error, train and test sets.mp4 4.4 MB
3. Generalization error, train and test sets.srt 2.8 KB
4. Generalization and Overfitting Demonstration in Code.mp4 17.2 MB
4. Generalization and Overfitting Demonstration in Code.srt 9.2 KB
5. Categorical inputs.mp4 8.2 MB
5. Categorical inputs.srt 4.8 KB
6. One-Hot Encoding Quiz.mp4 3.8 MB
6. One-Hot Encoding Quiz.srt 2.5 KB
7. Probabilistic Interpretation of Squared Error.mp4 8.1 MB
7. Probabilistic Interpretation of Squared Error.srt 6.4 KB
8. L2 Regularization - Theory.mp4 6.7 MB
8. L2 Regularization - Theory.srt 5.5 KB
9. L2 Regularization - Code.mp4 8.1 MB
9. L2 Regularization - Code.srt 3.4 KB
1. Brief overview of advanced linear regression and machine learning topics.mp4 8.1 MB
1. Brief overview of advanced linear regression and machine learning topics.srt 5.7 KB
2. Exercises, practice, and how to get good at this.mp4 7.2 MB
2. Exercises, practice, and how to get good at this.srt 5.3 KB
1. Anaconda Environment Setup.mp4 186.3 MB
1. Anaconda Environment Setup.srt 20.1 KB
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 43.9 MB
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14.5 KB
1. How to Code by Yourself (part 1).mp4 24.5 MB
1. How to Code by Yourself (part 1).srt 22.8 KB
2. How to Code by Yourself (part 2).mp4 14.8 MB
2. How to Code by Yourself (part 2).srt 13.3 KB
3. Proof that using Jupyter Notebook is the same as not using it.mp4 78.3 MB
3. Proof that using Jupyter Notebook is the same as not using it.srt 14.1 KB
4. Python 2 vs Python 3.mp4 7.8 MB
4. Python 2 vs Python 3.srt 6.1 KB
[Tutorialsplanet.NET].url 128 bytes
1. How to Succeed in this Course (Long Version).mp4 18.3 MB
1. How to Succeed in this Course (Long Version).srt 14.5 KB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39.0 MB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 31.8 KB
3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 29.3 MB
3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt 16.0 KB
4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 37.6 MB
4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt 23.0 KB
1. What is the Appendix.mp4 5.5 MB
1. What is the Appendix.srt 3.7 KB
2. BONUS.mp4 37.8 MB
2. BONUS.srt 7.9 KB
[Tutorialsplanet.NET].url 128 bytes

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