Udemy - Deep Learning Prerequisites Logistic Regression in Python (3.2020)

File Name

Size

1. Start Here/1. Introduction and Outline.mp4

47 MB

1. Start Here/1. Introduction and Outline.srt

5.3 kB

1. Start Here/2. How to Succeed in this Course.mp4

6.4 MB

1. Start Here/2. How to Succeed in this Course.srt

4.0 kB

1. Start Here/3. Review of the classification problem.mp4

3.0 MB

1. Start Here/3. Review of the classification problem.srt

2.2 kB

1. Start Here/4. Introduction to the E-Commerce Course Project.mp4

15 MB

1. Start Here/4. Introduction to the E-Commerce Course Project.srt

7.6 MB

1. Start Here/5. Easy first quiz.html

152 B

2. Basics What is linear classification What's the relation to neural networks/1. Linear Classification.mp4

7.6 MB

2. Basics What is linear classification What's the relation to neural networks/1. Linear Classification.srt

5.2 kB

2. Basics What is linear classification What's the relation to neural networks/2. Biological inspiration - the neuron.mp4

9.4 MB

2. Basics What is linear classification What's the relation to neural networks/2. Biological inspiration - the neuron.srt

4.4 kB

2. Basics What is linear classification What's the relation to neural networks/3. How do we calculate the output of a neuron logistic classifier - Theory.mp4

15 MB

2. Basics What is linear classification What's the relation to neural networks/3. How do we calculate the output of a neuron logistic classifier - Theory.srt

80 MB

2. Basics What is linear classification What's the relation to neural networks/4. How do we calculate the output of a neuron logistic classifier - Code.mp4

5.8 MB

2. Basics What is linear classification What's the relation to neural networks/4. How do we calculate the output of a neuron logistic classifier - Code.srt

4.5 kB

2. Basics What is linear classification What's the relation to neural networks/5. Interpretation of Logistic Regression Output.mp4

28 MB

2. Basics What is linear classification What's the relation to neural networks/5. Interpretation of Logistic Regression Output.srt

6.4 kB

2. Basics What is linear classification What's the relation to neural networks/6. E-Commerce Course Project Pre-Processing the Data.mp4

11 MB

2. Basics What is linear classification What's the relation to neural networks/6. E-Commerce Course Project Pre-Processing the Data.srt

5.1 kB

2. Basics What is linear classification What's the relation to neural networks/7. E-Commerce Course Project Making Predictions.mp4

5.7 MB

2. Basics What is linear classification What's the relation to neural networks/7. E-Commerce Course Project Making Predictions.srt

3.0 kB

2. Basics What is linear classification What's the relation to neural networks/8. Feedforward Quiz.mp4

2.3 MB

2. Basics What is linear classification What's the relation to neural networks/8. Feedforward Quiz.srt

1.7 kB

2. Basics What is linear classification What's the relation to neural networks/9. Prediction Section Summary.mp4

2.2 MB

2. Basics What is linear classification What's the relation to neural networks/9. Prediction Section Summary.srt

1.5 kB

3. Solving for the optimal weights/1. Training Section Introduction.mp4

2.8 MB

3. Solving for the optimal weights/1. Training Section Introduction.srt

2.0 kB

3. Solving for the optimal weights/10. E-Commerce Course Project Training the Logistic Model.mp4

17 MB

3. Solving for the optimal weights/10. E-Commerce Course Project Training the Logistic Model.srt

5.3 kB

3. Solving for the optimal weights/11. Training Section Summary.mp4

3.4 MB

3. Solving for the optimal weights/11. Training Section Summary.srt

2.6 kB

3. Solving for the optimal weights/2. A closed-form solution to the Bayes classifier.mp4

9.1 MB

3. Solving for the optimal weights/2. A closed-form solution to the Bayes classifier.srt

7.3 kB

3. Solving for the optimal weights/3. What do all these symbols mean X, Y, N, D, L, J, P(Y=1X), etc..mp4

6.4 MB

3. Solving for the optimal weights/3. What do all these symbols mean X, Y, N, D, L, J, P(Y=1X), etc..srt

5.2 kB

3. Solving for the optimal weights/4. The cross-entropy error function - Theory.mp4

4.5 MB

3. Solving for the optimal weights/4. The cross-entropy error function - Theory.srt

4.4 kB

3. Solving for the optimal weights/5. The cross-entropy error function - Code.mp4

9.1 MB

3. Solving for the optimal weights/5. The cross-entropy error function - Code.srt

3.9 kB

3. Solving for the optimal weights/6. Visualizing the linear discriminant Bayes classifier Gaussian clouds.mp4

5.3 MB

3. Solving for the optimal weights/6. Visualizing the linear discriminant Bayes classifier Gaussian clouds.srt

2.3 kB

3. Solving for the optimal weights/7. Maximizing the likelihood.mp4

25 MB

3. Solving for the optimal weights/7. Maximizing the likelihood.srt

4.0 kB

3. Solving for the optimal weights/8. Updating the weights using gradient descent - Theory.mp4

9.3 MB

3. Solving for the optimal weights/8. Updating the weights using gradient descent - Theory.srt

8.1 kB

3. Solving for the optimal weights/9. Updating the weights using gradient descent - Code.mp4

7.3 MB

3. Solving for the optimal weights/9. Updating the weights using gradient descent - Code.srt

2.5 kB

4. Practical concerns/1. Practical Section Introduction.mp4

4.7 MB

4. Practical concerns/1. Practical Section Introduction.srt

3.5 kB

4. Practical concerns/10. Why Divide by Square Root of D.mp4

24 MB

4. Practical concerns/10. Why Divide by Square Root of D.srt

8.7 kB

4. Practical concerns/11. Practical Section Summary.mp4

3.4 MB

4. Practical concerns/11. Practical Section Summary.srt

78 MB

4. Practical concerns/2. Interpreting the Weights.mp4

6.3 MB

4. Practical concerns/2. Interpreting the Weights.srt

4.7 kB

4. Practical concerns/3. L2 Regularization - Theory.mp4

15 MB

4. Practical concerns/3. L2 Regularization - Theory.srt

12 kB

4. Practical concerns/4. L2 Regularization - Code.mp4

4.5 MB

4. Practical concerns/4. L2 Regularization - Code.srt

1.6 kB

4. Practical concerns/5. L1 Regularization - Theory.mp4

4.4 MB

4. Practical concerns/5. L1 Regularization - Theory.srt

15 MB

4. Practical concerns/6. L1 Regularization - Code.mp4

12 MB

4. Practical concerns/6. L1 Regularization - Code.srt

4.6 kB

4. Practical concerns/7. L1 vs L2 Regularization.mp4

4.8 MB

4. Practical concerns/7. L1 vs L2 Regularization.srt

4.3 kB

4. Practical concerns/8. The donut problem.mp4

25 MB

4. Practical concerns/8. The donut problem.srt

7.4 kB

4. Practical concerns/9. The XOR problem.mp4

14 MB

4. Practical concerns/9. The XOR problem.srt

6.1 kB

5. Checkpoint and applications How to make sure you know your stuff/1. BONUS Sentiment Analysis.mp4

11 MB

5. Checkpoint and applications How to make sure you know your stuff/1. BONUS Sentiment Analysis.srt

6.4 kB

5. Checkpoint and applications How to make sure you know your stuff/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4

4.0 MB

5. Checkpoint and applications How to make sure you know your stuff/2. BONUS Where to get Udemy coupons and FREE deep learning material.srt

3.4 kB

5. Checkpoint and applications How to make sure you know your stuff/3. BONUS Exercises + how to get good at this.mp4

5.3 MB

5. Checkpoint and applications How to make sure you know your stuff/3. BONUS Exercises + how to get good at this.srt

3.8 kB

6. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.mp4

9.8 MB

6. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.srt

6.5 kB

6. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.mp4

21 MB

6. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.srt

16 kB

6. Project Facial Expression Recognition/3. The class imbalance problem.mp4

10 MB

6. Project Facial Expression Recognition/3. The class imbalance problem.srt

8.0 kB

6. Project Facial Expression Recognition/4. Utilities walkthrough.mp4

14 MB

6. Project Facial Expression Recognition/4. Utilities walkthrough.srt

5.8 kB

6. Project Facial Expression Recognition/5. Facial Expression Recognition in Code.mp4

24 MB

6. Project Facial Expression Recognition/5. Facial Expression Recognition in Code.srt

8.1 kB

6. Project Facial Expression Recognition/6. Facial Expression Recognition Project Summary.mp4

2.9 MB

6. Project Facial Expression Recognition/6. Facial Expression Recognition Project Summary.srt

1.7 kB

7. Appendix FAQ/1. What is the Appendix.mp4

5.5 MB

7. Appendix FAQ/1. What is the Appendix.srt

3.8 kB

7. Appendix FAQ/10. Proof that using Jupyter Notebook is the same as not using it.mp4

78 MB

7. Appendix FAQ/10. Proof that using Jupyter Notebook is the same as not using it.srt

78 MB

7. Appendix FAQ/11. Python 2 vs Python 3.mp4

7.8 MB

7. Appendix FAQ/11. Python 2 vs Python 3.srt

6.6 kB

7. Appendix FAQ/12. What order should I take your courses in (part 1).mp4

29 MB

7. Appendix FAQ/12. What order should I take your courses in (part 1).srt

17 kB

7. Appendix FAQ/13. What order should I take your courses in (part 2).mp4

38 MB

7. Appendix FAQ/13. What order should I take your courses in (part 2).srt

25 kB

7. Appendix FAQ/14. BONUS Where to get discount coupons and FREE deep learning material.mp4

38 MB

7. Appendix FAQ/14. BONUS Where to get discount coupons and FREE deep learning material.srt

8.4 kB

7. Appendix FAQ/2. Gradient Descent Tutorial.mp4

23 MB

7. Appendix FAQ/2. Gradient Descent Tutorial.srt

5.9 kB

7. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4

186 MB

7. Appendix FAQ/3. Windows-Focused Environment Setup 2018.srt

22 kB

7. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4

44 MB

7. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt

16 kB

7. Appendix FAQ/5. How to Code by Yourself (part 1).mp4

24 MB

7. Appendix FAQ/5. How to Code by Yourself (part 1).srt

24 kB

7. Appendix FAQ/6. How to Code by Yourself (part 2).mp4

15 MB

7. Appendix FAQ/6. How to Code by Yourself (part 2).srt

14 kB

7. Appendix FAQ/7. How to Uncompress a .tar.gz file.mp4

5.4 MB

7. Appendix FAQ/7. How to Uncompress a .tar.gz file.srt

4.4 kB

7. Appendix FAQ/8. How to Succeed in this Course (Long Version).mp4

13 MB

7. Appendix FAQ/8. How to Succeed in this Course (Long Version).srt

16 kB

7. Appendix FAQ/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4

39 MB

7. Appendix FAQ/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt

34 kB