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[Tutorialsplanet.NET] Udemy - Deep Learning Prerequisites Linear Regression in Python

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File Name
Size
1. Welcome/1. Introduction and Outline.mp4
43 MB
1. Welcome/1. Introduction and Outline.srt
11 kB
1. Welcome/2. How to Succeed in this Course.mp4
44 MB
1. Welcome/2. How to Succeed in this Course.srt
8.3 kB
1. Welcome/3. Statistics vs. Machine Learning.mp4
56 MB
1. Welcome/3. Statistics vs. Machine Learning.srt
15 kB
1. Welcome/[Tutorialsplanet.NET].url
128 B
2. 1-D Linear Regression Theory and Code/1. What is machine learning How does linear regression play a role.mp4
8.4 MB
2. 1-D Linear Regression Theory and Code/1. What is machine learning How does linear regression play a role.srt
5.8 kB
2. 1-D Linear Regression Theory and Code/10. Demonstrating Moore's Law in Code.mp4
18 MB
2. 1-D Linear Regression Theory and Code/10. Demonstrating Moore's Law in Code.srt
6.9 kB
2. 1-D Linear Regression Theory and Code/11. Moore's Law Derivation.mp4
20 MB
2. 1-D Linear Regression Theory and Code/11. Moore's Law Derivation.srt
7.6 kB
2. 1-D Linear Regression Theory and Code/12. R-squared Quiz 1.mp4
2.8 MB
2. 1-D Linear Regression Theory and Code/12. R-squared Quiz 1.srt
2.2 kB
2. 1-D Linear Regression Theory and Code/13. Suggestion Box.mp4
16 MB
2. 1-D Linear Regression Theory and Code/13. Suggestion Box.srt
4.7 kB
2. 1-D Linear Regression Theory and Code/2. What can linear regression be used for.html
150 B
2. 1-D Linear Regression Theory and Code/3. Define the model in 1-D, derive the solution (Updated Version).mp4
19 MB
2. 1-D Linear Regression Theory and Code/3. Define the model in 1-D, derive the solution (Updated Version).srt
16 kB
2. 1-D Linear Regression Theory and Code/4. Define the model in 1-D, derive the solution.mp4
25 MB
2. 1-D Linear Regression Theory and Code/4. Define the model in 1-D, derive the solution.srt
11 kB
2. 1-D Linear Regression Theory and Code/5. Coding the 1-D solution in Python.mp4
14 MB
2. 1-D Linear Regression Theory and Code/5. Coding the 1-D solution in Python.srt
5.6 kB
2. 1-D Linear Regression Theory and Code/6. Exercise Theory vs. Code.mp4
1.0 MB
2. 1-D Linear Regression Theory and Code/6. Exercise Theory vs. Code.srt
1.6 kB
2. 1-D Linear Regression Theory and Code/7. Determine how good the model is - r-squared.mp4
11 MB
2. 1-D Linear Regression Theory and Code/7. Determine how good the model is - r-squared.srt
4.7 kB
2. 1-D Linear Regression Theory and Code/8. R-squared in code.mp4
4.5 MB
2. 1-D Linear Regression Theory and Code/8. R-squared in code.srt
1.7 kB
2. 1-D Linear Regression Theory and Code/9. Introduction to Moore's Law Problem.mp4
4.4 MB
2. 1-D Linear Regression Theory and Code/9. Introduction to Moore's Law Problem.srt
3.7 kB
3. Multiple linear regression and polynomial regression/1. Define the multi-dimensional problem and derive the solution (Updated Version).mp4
14 MB
3. Multiple linear regression and polynomial regression/1. Define the multi-dimensional problem and derive the solution (Updated Version).srt
12 kB
3. Multiple linear regression and polynomial regression/2. Define the multi-dimensional problem and derive the solution.mp4
36 MB
3. Multiple linear regression and polynomial regression/2. Define the multi-dimensional problem and derive the solution.srt
13 kB
3. Multiple linear regression and polynomial regression/3. How to solve multiple linear regression using only matrices.mp4
3.1 MB
3. Multiple linear regression and polynomial regression/3. How to solve multiple linear regression using only matrices.srt
2.0 kB
3. Multiple linear regression and polynomial regression/4. Coding the multi-dimensional solution in Python.mp4
15 MB
3. Multiple linear regression and polynomial regression/4. Coding the multi-dimensional solution in Python.srt
5.2 kB
3. Multiple linear regression and polynomial regression/5. Polynomial regression - extending linear regression (with Python code).mp4
16 MB
3. Multiple linear regression and polynomial regression/5. Polynomial regression - extending linear regression (with Python code).srt
4.9 kB
3. Multiple linear regression and polynomial regression/6. Predicting Systolic Blood Pressure from Age and Weight.mp4
12 MB
3. Multiple linear regression and polynomial regression/6. Predicting Systolic Blood Pressure from Age and Weight.srt
5.5 kB
3. Multiple linear regression and polynomial regression/7. R-squared Quiz 2.mp4
3.5 MB
3. Multiple linear regression and polynomial regression/7. R-squared Quiz 2.srt
2.7 kB
4. Practical machine learning issues/1. What do all these letters mean.mp4
9.6 MB
4. Practical machine learning issues/1. What do all these letters mean.srt
8.0 kB
4. Practical machine learning issues/10. The Dummy Variable Trap.mp4
6.1 MB
4. Practical machine learning issues/10. The Dummy Variable Trap.srt
5.5 kB
4. Practical machine learning issues/11. Gradient Descent Tutorial.mp4
23 MB
4. Practical machine learning issues/11. Gradient Descent Tutorial.srt
5.5 kB
4. Practical machine learning issues/12. Gradient Descent for Linear Regression.mp4
3.5 MB
4. Practical machine learning issues/12. Gradient Descent for Linear Regression.srt
3.1 kB
4. Practical machine learning issues/13. Bypass the Dummy Variable Trap with Gradient Descent.mp4
8.5 MB
4. Practical machine learning issues/13. Bypass the Dummy Variable Trap with Gradient Descent.srt
3.6 kB
4. Practical machine learning issues/14. L1 Regularization - Theory.mp4
4.7 MB
4. Practical machine learning issues/14. L1 Regularization - Theory.srt
4.1 kB
4. Practical machine learning issues/15. L1 Regularization - Code.mp4
8.3 MB
4. Practical machine learning issues/15. L1 Regularization - Code.srt
3.5 kB
4. Practical machine learning issues/16. L1 vs L2 Regularization.mp4
4.8 MB
4. Practical machine learning issues/16. L1 vs L2 Regularization.srt
4.3 kB
4. Practical machine learning issues/17. Why Divide by Square Root of D.mp4
24 MB
4. Practical machine learning issues/17. Why Divide by Square Root of D.srt
8.7 kB
4. Practical machine learning issues/2. Interpreting the Weights.mp4
14 MB
4. Practical machine learning issues/2. Interpreting the Weights.srt
4.3 kB
4. Practical machine learning issues/3. Generalization error, train and test sets.mp4
4.4 MB
4. Practical machine learning issues/3. Generalization error, train and test sets.srt
2.8 kB
4. Practical machine learning issues/4. Generalization and Overfitting Demonstration in Code.mp4
17 MB
4. Practical machine learning issues/4. Generalization and Overfitting Demonstration in Code.srt
9.2 kB
4. Practical machine learning issues/5. Categorical inputs.mp4
8.2 MB
4. Practical machine learning issues/5. Categorical inputs.srt
4.8 kB
4. Practical machine learning issues/6. One-Hot Encoding Quiz.mp4
3.8 MB
4. Practical machine learning issues/6. One-Hot Encoding Quiz.srt
2.5 kB
4. Practical machine learning issues/7. Probabilistic Interpretation of Squared Error.mp4
8.1 MB
4. Practical machine learning issues/7. Probabilistic Interpretation of Squared Error.srt
6.4 kB
4. Practical machine learning issues/8. L2 Regularization - Theory.mp4
6.7 MB
4. Practical machine learning issues/8. L2 Regularization - Theory.srt
5.5 kB
4. Practical machine learning issues/9. L2 Regularization - Code.mp4
8.1 MB
4. Practical machine learning issues/9. L2 Regularization - Code.srt
3.4 kB
5. Conclusion and Next Steps/1. Brief overview of advanced linear regression and machine learning topics.mp4
8.1 MB
5. Conclusion and Next Steps/1. Brief overview of advanced linear regression and machine learning topics.srt
5.7 kB
5. Conclusion and Next Steps/2. Exercises, practice, and how to get good at this.mp4
7.2 MB
5. Conclusion and Next Steps/2. Exercises, practice, and how to get good at this.srt
5.3 kB
6. Setting Up Your Environment (FAQ by Student Request)/1. Anaconda Environment Setup.mp4
186 MB
6. Setting Up Your Environment (FAQ by Student Request)/1. Anaconda Environment Setup.srt
20 kB
6. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
44 MB
6. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt
14 kB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code by Yourself (part 1).mp4
24 MB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code by Yourself (part 1).srt
23 kB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code by Yourself (part 2).mp4
15 MB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code by Yourself (part 2).srt
13 kB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. Proof that using Jupyter Notebook is the same as not using it.mp4
78 MB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. Proof that using Jupyter Notebook is the same as not using it.srt
14 kB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Python 2 vs Python 3.mp4
7.8 MB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Python 2 vs Python 3.srt
6.1 kB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/[Tutorialsplanet.NET].url
128 B
8/1. How to Succeed in this Course (Long Version).mp4
18 MB
8/1. How to Succeed in this Course (Long Version).srt
14 kB
8/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4
39 MB
8/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt
32 kB
8/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4
29 MB
8/3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt
16 kB
8/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4
38 MB
8/4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt
23 kB
9. Appendix FAQ Finale/1. What is the Appendix.mp4
5.5 MB
9. Appendix FAQ Finale/1. What is the Appendix.srt
3.7 kB
9. Appendix FAQ Finale/2. BONUS.mp4
38 MB
9. Appendix FAQ Finale/2. BONUS.srt
7.9 kB
[Tutorialsplanet.NET].url
128 B