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

Creation Time	Dec. 26, 2025, 12:02 a.m.
Last Access Time	Jan. 11, 2026, 1:05 a.m.
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Keywords	Tutorialsplanet Logistic Prerequisites - Deep Udemy Python Learning in NET Regression
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Total Files	114
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8. Setting Up Your Environment/1. Windows-Focused Environment Setup 2018.mp4 186.3 MB
9. Extra Help With Python Coding for Beginners/4. Proof that using Jupyter Notebook is the same as not using it.mp4 78.3 MB
3/2. Define the multi-dimensional problem and derive the solution.mp4 60.3 MB
1. Start Here/3. Statistics vs. Machine Learning.mp4 55.6 MB
8. Setting Up Your Environment/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 43.9 MB
10. Effective Learning Strategies for Machine Learning/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39.0 MB
11. Appendix FAQ/2. BONUS Where to get discount coupons and FREE deep learning material.mp4 37.8 MB
10. Effective Learning Strategies for Machine Learning/4. What order should I take your courses in (part 2).mp4 37.6 MB
10. Effective Learning Strategies for Machine Learning/3. What order should I take your courses in (part 1).mp4 29.3 MB
1. Start Here/2. How to Succeed in this Course.mp4 28.0 MB
4. Practical concerns/8. The donut problem.mp4 24.7 MB
2/2. Define the model in 1-D, derive the solution.mp4 24.7 MB
9. Extra Help With Python Coding for Beginners/2. How to Code by Yourself (part 1).mp4 24.5 MB
6. Project Facial Expression Recognition/5. Facial Expression Recognition in Code.mp4 24.0 MB
4. Practical concerns/10. Why Divide by Square Root of D.mp4 23.5 MB
7. Background Review/1. Gradient Descent Tutorial.mp4 22.8 MB
6. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.mp4 21.4 MB
2/9. Moore's Law Derivation.mp4 20.2 MB
2/5. Determine how good the model is - r-squared.mp4 19.7 MB
2/1. Define the model in 1-D, derive the solution (Updated Version).mp4 19.4 MB
2/8. Demonstrating Moore's Law in Code.mp4 17.5 MB
3/5. Polynomial regression - extending linear regression (with Python code).mp4 16.4 MB
2/11. Suggestion Box.mp4 16.1 MB
3/4. Coding the multi-dimensional solution in Python.mp4 14.9 MB
9. Extra Help With Python Coding for Beginners/3. How to Code by Yourself (part 2).mp4 14.8 MB
1. Start Here/5. Introduction to the E-Commerce Course Project.mp4 14.8 MB
4. Practical concerns/3. L2 Regularization - Theory.mp4 14.7 MB
3/1. Define the multi-dimensional problem and derive the solution (Updated Version).mp4 14.4 MB
2/3. Coding the 1-D solution in Python.mp4 14.4 MB
4. Practical concerns/9. The XOR problem.mp4 14.2 MB
1. Start Here/1. Introduction and Outline.mp4 14.0 MB
6. Project Facial Expression Recognition/4. Utilities walkthrough.mp4 13.5 MB
10. Effective Learning Strategies for Machine Learning/1. How to Succeed in this Course (Long Version).mp4 13.0 MB
3/6. Predicting Systolic Blood Pressure from Age and Weight.mp4 12.3 MB
4. Practical concerns/6. L1 Regularization - Code.mp4 12.0 MB
5. Checkpoint and applications How to make sure you know your stuff/1. BONUS Sentiment Analysis.mp4 11.4 MB
6. Project Facial Expression Recognition/3. The class imbalance problem.mp4 10.1 MB
6. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.mp4 9.8 MB
9. Extra Help With Python Coding for Beginners/5. Python 2 vs Python 3.mp4 7.8 MB
4. Practical concerns/2. Interpreting the Weights.mp4 6.3 MB
11. Appendix FAQ/1. What is the Appendix.mp4 5.5 MB
9. Extra Help With Python Coding for Beginners/1. How to Uncompress a .tar.gz file.mp4 5.4 MB
5. Checkpoint and applications How to make sure you know your stuff/2. BONUS Exercises + how to get good at this.mp4 5.3 MB
4. Practical concerns/7. L1 vs L2 Regularization.mp4 4.8 MB
4. Practical concerns/1. Practical Section Introduction.mp4 4.7 MB
2/6. R-squared in code.mp4 4.5 MB
4. Practical concerns/4. L2 Regularization - Code.mp4 4.5 MB
4. Practical concerns/5. L1 Regularization - Theory.mp4 4.4 MB
2/7. Introduction to Moore's Law Problem.mp4 4.4 MB
3/7. R-squared Quiz 2.mp4 3.5 MB
4. Practical concerns/11. Practical Section Summary.mp4 3.4 MB
3/3. How to solve multiple linear regression using only matrices.mp4 3.1 MB
1. Start Here/4. Review of the classification problem.mp4 3.0 MB
6. Project Facial Expression Recognition/6. Facial Expression Recognition Project Summary.mp4 2.9 MB
2/10. R-squared Quiz 1.mp4 2.8 MB
2/4. Exercise Theory vs. Code.mp4 1.0 MB
10. Effective Learning Strategies for Machine Learning/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 33.9 KB
10. Effective Learning Strategies for Machine Learning/4. What order should I take your courses in (part 2).srt 25.1 KB
9. Extra Help With Python Coding for Beginners/2. How to Code by Yourself (part 1).srt 24.3 KB
8. Setting Up Your Environment/1. Windows-Focused Environment Setup 2018.srt 21.6 KB
2/1. Define the model in 1-D, derive the solution (Updated Version).srt 17.7 KB
10. Effective Learning Strategies for Machine Learning/3. What order should I take your courses in (part 1).srt 17.1 KB
1. Start Here/3. Statistics vs. Machine Learning.srt 16.0 KB
6. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.srt 16.0 KB
10. Effective Learning Strategies for Machine Learning/1. How to Succeed in this Course (Long Version).srt 15.5 KB
8. Setting Up Your Environment/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 15.5 KB
9. Extra Help With Python Coding for Beginners/4. Proof that using Jupyter Notebook is the same as not using it.srt 15.1 KB
9. Extra Help With Python Coding for Beginners/3. How to Code by Yourself (part 2).srt 14.0 KB
1. Start Here/5. Introduction to the E-Commerce Course Project.srt 14.0 KB
3/2. Define the multi-dimensional problem and derive the solution.srt 12.9 KB
3/1. Define the multi-dimensional problem and derive the solution (Updated Version).srt 12.5 KB
4. Practical concerns/3. L2 Regularization - Theory.srt 11.5 KB
2/2. Define the model in 1-D, derive the solution.srt 11.1 KB
4. Practical concerns/10. Why Divide by Square Root of D.srt 9.4 KB
1. Start Here/2. How to Succeed in this Course.srt 9.3 KB
11. Appendix FAQ/2. BONUS Where to get discount coupons and FREE deep learning material.srt 8.4 KB
2/9. Moore's Law Derivation.srt 8.1 KB
6. Project Facial Expression Recognition/5. Facial Expression Recognition in Code.srt 8.1 KB
6. Project Facial Expression Recognition/3. The class imbalance problem.srt 8.0 KB
4. Practical concerns/8. The donut problem.srt 7.4 KB
2/8. Demonstrating Moore's Law in Code.srt 6.9 KB
6. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.srt 6.9 KB
9. Extra Help With Python Coding for Beginners/5. Python 2 vs Python 3.srt 6.6 KB
5. Checkpoint and applications How to make sure you know your stuff/1. BONUS Sentiment Analysis.srt 6.4 KB
4. Practical concerns/9. The XOR problem.srt 6.1 KB
7. Background Review/1. Gradient Descent Tutorial.srt 5.9 KB
2/3. Coding the 1-D solution in Python.srt 5.9 KB
6. Project Facial Expression Recognition/4. Utilities walkthrough.srt 5.8 KB
3/4. Coding the multi-dimensional solution in Python.srt 5.5 KB
3/6. Predicting Systolic Blood Pressure from Age and Weight.srt 5.5 KB
1. Start Here/1. Introduction and Outline.srt 5.3 KB
3/5. Polynomial regression - extending linear regression (with Python code).srt 5.3 KB
4. Practical concerns/2. Interpreting the Weights.srt 5.0 KB
4. Practical concerns/6. L1 Regularization - Code.srt 4.9 KB
2/11. Suggestion Box.srt 4.9 KB
2/5. Determine how good the model is - r-squared.srt 4.7 KB
4. Practical concerns/7. L1 vs L2 Regularization.srt 4.4 KB
9. Extra Help With Python Coding for Beginners/1. How to Uncompress a .tar.gz file.srt 4.4 KB
4. Practical concerns/5. L1 Regularization - Theory.srt 4.0 KB
5. Checkpoint and applications How to make sure you know your stuff/2. BONUS Exercises + how to get good at this.srt 3.8 KB
11. Appendix FAQ/1. What is the Appendix.srt 3.8 KB
4. Practical concerns/1. Practical Section Introduction.srt 3.8 KB
2/7. Introduction to Moore's Law Problem.srt 3.7 KB
3/7. R-squared Quiz 2.srt 2.9 KB
4. Practical concerns/11. Practical Section Summary.srt 2.7 KB
1. Start Here/4. Review of the classification problem.srt 2.4 KB
2/10. R-squared Quiz 1.srt 2.4 KB
3/3. How to solve multiple linear regression using only matrices.srt 2.0 KB
2/6. R-squared in code.srt 1.8 KB
6. Project Facial Expression Recognition/6. Facial Expression Recognition Project Summary.srt 1.7 KB
4. Practical concerns/4. L2 Regularization - Code.srt 1.6 KB
2/4. Exercise Theory vs. Code.srt 1.6 KB
1. Start Here/6. Easy first quiz.html 152 bytes
[Tutorialsplanet.NET].url 128 bytes

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

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