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[Tutorialsplanet.NET] Udemy - Deep Learning Prerequisites Linear Regression in Python
magnet:?xt=urn:btih:32b7bb017c4d88324beb30985a2197892d23a92e&dn=[Tutorialsplanet.NET] Udemy - Deep Learning Prerequisites Linear Regression in Python
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Hash值:
32b7bb017c4d88324beb30985a2197892d23a92e
点击数:
259
文件大小:
1.11 GB
文件数量:
54
创建日期:
2021-7-13 16:39
最后访问:
2024-7-17 07:45
访问标签:
Tutorialsplanet
NET
Udemy
-
Deep
Learning
Prerequisites
Linear
Regression
in
Python
文件列表详情
1. Welcome/1. Welcome.mp4 49.68 MB
1. Welcome/2. Introduction and Outline.mp4 6.34 MB
1. Welcome/3. What is machine learning How does linear regression play a role.mp4 8.43 MB
1. Welcome/4. Anyone Can Succeed in this Course.mp4 83.98 MB
1. Welcome/5. Statistics vs. Machine Learning.mp4 55.52 MB
2. 1-D Linear Regression Theory and Code/1. Define the model in 1-D, derive the solution (Updated Version).mp4 19.34 MB
2. 1-D Linear Regression Theory and Code/10. R-squared Quiz 1.mp4 2.8 MB
2. 1-D Linear Regression Theory and Code/11. Suggestion Box.mp4 16.08 MB
2. 1-D Linear Regression Theory and Code/2. Define the model in 1-D, derive the solution.mp4 24.66 MB
2. 1-D Linear Regression Theory and Code/3. Coding the 1-D solution in Python.mp4 14.43 MB
2. 1-D Linear Regression Theory and Code/4. Exercise Theory vs. Code.mp4 1.05 MB
2. 1-D Linear Regression Theory and Code/5. Determine how good the model is - r-squared.mp4 11.3 MB
2. 1-D Linear Regression Theory and Code/6. R-squared in code.mp4 4.5 MB
2. 1-D Linear Regression Theory and Code/7. Introduction to Moore's Law Problem.mp4 4.41 MB
2. 1-D Linear Regression Theory and Code/8. Demonstrating Moore's Law in Code.mp4 17.51 MB
2. 1-D Linear Regression Theory and Code/9. Moore's Law Derivation.mp4 20.18 MB
3. Multiple linear regression and polynomial regression/1. Define the multi-dimensional problem and derive the solution (Updated Version).mp4 14.44 MB
3. Multiple linear regression and polynomial regression/2. Define the multi-dimensional problem and derive the solution.mp4 36.08 MB
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/4. Coding the multi-dimensional solution in Python.mp4 14.92 MB
3. Multiple linear regression and polynomial regression/5. Polynomial regression - extending linear regression (with Python code).mp4 16.4 MB
3. Multiple linear regression and polynomial regression/6. Predicting Systolic Blood Pressure from Age and Weight.mp4 12.34 MB
3. Multiple linear regression and polynomial regression/7. R-squared Quiz 2.mp4 3.5 MB
4. Practical machine learning issues/1. What do all these letters mean.mp4 9.63 MB
4. Practical machine learning issues/10. The Dummy Variable Trap.mp4 6.07 MB
4. Practical machine learning issues/11. Gradient Descent Tutorial.mp4 22.8 MB
4. Practical machine learning issues/12. Gradient Descent for Linear Regression.mp4 3.51 MB
4. Practical machine learning issues/13. Bypass the Dummy Variable Trap with Gradient Descent.mp4 8.5 MB
4. Practical machine learning issues/14. L1 Regularization - Theory.mp4 4.66 MB
4. Practical machine learning issues/15. L1 Regularization - Code.mp4 8.26 MB
4. Practical machine learning issues/16. L1 vs L2 Regularization.mp4 4.8 MB
4. Practical machine learning issues/17. Why Divide by Square Root of D.mp4 23.49 MB
4. Practical machine learning issues/2. Interpreting the Weights.mp4 14.15 MB
4. Practical machine learning issues/3. Generalization error, train and test sets.mp4 4.39 MB
4. Practical machine learning issues/4. Generalization and Overfitting Demonstration in Code.mp4 17.25 MB
4. Practical machine learning issues/5. Categorical inputs.mp4 8.18 MB
4. Practical machine learning issues/6. One-Hot Encoding Quiz.mp4 3.78 MB
4. Practical machine learning issues/7. Probabilistic Interpretation of Squared Error.mp4 8.13 MB
4. Practical machine learning issues/8. L2 Regularization - Theory.mp4 6.65 MB
4. Practical machine learning issues/9. L2 Regularization - Code.mp4 8.08 MB
5. Conclusion and Next Steps/1. Brief overview of advanced linear regression and machine learning topics.mp4 8.13 MB
5. Conclusion and Next Steps/2. Exercises, practice, and how to get good at this.mp4 7.16 MB
6. Setting Up Your Environment (FAQ by Student Request)/1. Windows-Focused Environment Setup 2018.mp4 186.29 MB
6. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 43.92 MB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code by Yourself (part 1).mp4 24.54 MB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code by Yourself (part 2).mp4 14.81 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.mp4 78.28 MB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Python 2 vs Python 3.mp4 7.83 MB
8/1. How to Succeed in this Course (Long Version).mp4 18.32 MB
8/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 38.95 MB
8/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 29.32 MB
8/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 37.62 MB
9. Appendix FAQ Finale/1. What is the Appendix.mp4 5.45 MB
9. Appendix FAQ Finale/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 37.83 MB
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