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Download [GigaCourse.com] Udemy - Deep Learning Prerequisites Logistic Regression in Python

GigaCourse com Udemy Deep Learning Prerequisites Logistic Regression in Python

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[GigaCourse.com] Udemy - Deep Learning Prerequisites Logistic Regression in Python

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Total Size

1.3 GB

Total Files

119

Last Seen

2024-09-19 02:25

Hash

F1121C4C04E049A209C8BC475237206093946943

/1. Start Here/

1. Introduction and Outline.mp4

49.2 MB

1. Introduction and Outline.srt

5.4 KB

2. How to Succeed in this Course.mp4

6.7 MB

2. How to Succeed in this Course.srt

4.1 KB

3. Review of the classification problem.mp4

3.1 MB

3. Review of the classification problem.srt

2.3 KB

4. Introduction to the E-Commerce Course Project.mp4

15.5 MB

4. Introduction to the E-Commerce Course Project.srt

8.0 MB

5. Easy first quiz.html

0.2 KB

/2. Basics What is linear classification What's the relation to neural networks/

1. Linear Classification.mp4

7.9 MB

1. Linear Classification.srt

5.3 KB

2. Biological inspiration - the neuron.mp4

9.8 MB

2. Biological inspiration - the neuron.srt

4.5 KB

3. How do we calculate the output of a neuron logistic classifier - Theory.mp4

16.0 MB

3. How do we calculate the output of a neuron logistic classifier - Theory.srt

84.1 MB

4. How do we calculate the output of a neuron logistic classifier - Code.mp4

6.1 MB

4. How do we calculate the output of a neuron logistic classifier - Code.srt

4.6 KB

5. Interpretation of Logistic Regression Output.mp4

29.2 MB

5. Interpretation of Logistic Regression Output.srt

6.5 KB

6. E-Commerce Course Project Pre-Processing the Data.mp4

11.7 MB

6. E-Commerce Course Project Pre-Processing the Data.srt

5.3 KB

7. E-Commerce Course Project Making Predictions.mp4

6.0 MB

7. E-Commerce Course Project Making Predictions.srt

3.1 KB

8. Feedforward Quiz.mp4

2.4 MB

8. Feedforward Quiz.srt

1.7 KB

9. Prediction Section Summary.mp4

2.3 MB

9. Prediction Section Summary.srt

1.5 KB

/3. Solving for the optimal weights/

1. Training Section Introduction.mp4

3.0 MB

1. Training Section Introduction.srt

2.1 KB

10. E-Commerce Course Project Training the Logistic Model.mp4

17.9 MB

10. E-Commerce Course Project Training the Logistic Model.srt

5.4 KB

11. Training Section Summary.mp4

3.6 MB

11. Training Section Summary.srt

2.7 KB

2. A closed-form solution to the Bayes classifier.mp4

9.5 MB

2. A closed-form solution to the Bayes classifier.srt

7.5 KB

3. What do all these symbols mean X, Y, N, D, L, J, P(Y=1X), etc..mp4

6.7 MB

3. What do all these symbols mean X, Y, N, D, L, J, P(Y=1X), etc..srt

5.3 KB

4. The cross-entropy error function - Theory.mp4

4.7 MB

4. The cross-entropy error function - Theory.srt

4.5 KB

5. The cross-entropy error function - Code.mp4

9.5 MB

5. The cross-entropy error function - Code.srt

4.0 KB

6. Visualizing the linear discriminant Bayes classifier Gaussian clouds.mp4

5.5 MB

6. Visualizing the linear discriminant Bayes classifier Gaussian clouds.srt

2.3 KB

7. Maximizing the likelihood.mp4

26.4 MB

7. Maximizing the likelihood.srt

4.1 KB

8. Updating the weights using gradient descent - Theory.mp4

9.8 MB

8. Updating the weights using gradient descent - Theory.srt

8.3 KB

9. Updating the weights using gradient descent - Code.mp4

7.6 MB

9. Updating the weights using gradient descent - Code.srt

2.5 KB

/4. Practical concerns/

1. Practical Section Introduction.mp4

5.0 MB

1. Practical Section Introduction.srt

3.6 KB

10. Why Divide by Square Root of D.mp4

24.6 MB

10. Why Divide by Square Root of D.srt

8.9 KB

11. Practical Section Summary.mp4

3.6 MB

11. Practical Section Summary.srt

82.1 MB

2. Interpreting the Weights.mp4

6.6 MB

2. Interpreting the Weights.srt

4.8 KB

3. L2 Regularization - Theory.mp4

15.4 MB

3. L2 Regularization - Theory.srt

11.8 KB

4. L2 Regularization - Code.mp4

4.7 MB

4. L2 Regularization - Code.srt

1.7 KB

5. L1 Regularization - Theory.mp4

4.6 MB

5. L1 Regularization - Theory.srt

15.7 MB

6. L1 Regularization - Code.mp4

12.6 MB

6. L1 Regularization - Code.srt

4.7 KB

7. L1 vs L2 Regularization.mp4

5.0 MB

7. L1 vs L2 Regularization.srt

4.4 KB

8. The donut problem.mp4

25.9 MB

8. The donut problem.srt

7.5 KB

9. The XOR problem.mp4

14.9 MB

9. The XOR problem.srt

6.2 KB

/5. Checkpoint and applications How to make sure you know your stuff/

1. BONUS Sentiment Analysis.mp4

12.0 MB

1. BONUS Sentiment Analysis.srt

6.6 KB

2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4

4.2 MB

2. BONUS Where to get Udemy coupons and FREE deep learning material.srt

3.5 KB

3. BONUS Exercises + how to get good at this.mp4

5.5 MB

3. BONUS Exercises + how to get good at this.srt

3.9 KB

/6. Project Facial Expression Recognition/

1. Facial Expression Recognition Project Introduction.mp4

10.3 MB

1. Facial Expression Recognition Project Introduction.srt

6.6 KB

2. Facial Expression Recognition Problem Description.mp4

22.5 MB

2. Facial Expression Recognition Problem Description.srt

16.4 KB

3. The class imbalance problem.mp4

10.6 MB

3. The class imbalance problem.srt

8.1 KB

4. Utilities walkthrough.mp4

14.1 MB

4. Utilities walkthrough.srt

6.0 KB

5. Facial Expression Recognition in Code.mp4

25.2 MB

5. Facial Expression Recognition in Code.srt

8.3 KB

6. Facial Expression Recognition Project Summary.mp4

3.1 MB

6. Facial Expression Recognition Project Summary.srt

1.8 KB

/7. Appendix FAQ/

1. What is the Appendix.mp4

5.7 MB

1. What is the Appendix.srt

3.9 KB

10. Proof that using Jupyter Notebook is the same as not using it.mp4

82.1 MB

10. Proof that using Jupyter Notebook is the same as not using it.srt

82.1 MB

11. Python 2 vs Python 3.mp4

8.2 MB

11. Python 2 vs Python 3.srt

6.8 KB

12. What order should I take your courses in (part 1).mp4

30.7 MB

12. What order should I take your courses in (part 1).srt

17.5 KB

13. What order should I take your courses in (part 2).mp4

39.4 MB

13. What order should I take your courses in (part 2).srt

25.7 KB

14. BONUS Where to get discount coupons and FREE deep learning material.mp4

39.7 MB

14. BONUS Where to get discount coupons and FREE deep learning material.srt

8.6 KB

2. Gradient Descent Tutorial.mp4

23.9 MB

2. Gradient Descent Tutorial.srt

6.1 KB

3. Windows-Focused Environment Setup 2018.mp4

195.3 MB

3. Windows-Focused Environment Setup 2018.srt

22.2 KB

4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4

46.1 MB

4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt

15.8 KB

5. How to Code by Yourself (part 1).mp4

25.7 MB

5. How to Code by Yourself (part 1).srt

24.9 KB

6. How to Code by Yourself (part 2).mp4

15.5 MB

6. How to Code by Yourself (part 2).srt

14.4 KB

7. How to Uncompress a .tar.gz file.mp4

5.7 MB

7. How to Uncompress a .tar.gz file.srt

4.5 KB

8. How to Succeed in this Course (Long Version).mp4

13.6 MB

8. How to Succeed in this Course (Long Version).srt

15.9 KB

9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4

40.9 MB

9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt

34.7 KB

/

Readme.txt

1.0 KB

[GigaCourse.com].url

0.0 KB

 

Total files 119


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