[GigaCourse.com] Udemy - Deep Learning Prerequisites Logistic Regression in Python torrent, magnet, bt

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

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F1121C4C04E049A209C8BC475237206093946943

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119

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1.25GB

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2020-06-25

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GigaCourse com Udemy Deep Learning Prerequisites Logistic Regression in Python

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File Name

Size

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

46.92MB

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

5.31KB

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

6.41MB

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

4.04KB

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

2.97MB

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

2.22KB

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

14.79MB

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

7.63MB

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

152B

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

7.55MB

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

5.17KB

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

9.39MB

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

4.37KB

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

15.22MB

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

80.18MB

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

5.82MB

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

4.49KB

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

27.89MB

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

6.38KB

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

11.17MB

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

5.13KB

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

5.7MB

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

3KB

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

2.27MB

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

1.69KB

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

2.22MB

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

1.47KB

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

2.81MB

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

2.05KB

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

17.06MB

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

5.26KB

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

3.39MB

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

2.59KB

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

9.11MB

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

7.33KB

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

6.37MB

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

5.21KB

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

4.5MB

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

4.39KB

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

9.1MB

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

3.94KB

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

5.27MB

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

2.29KB

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

25.22MB

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

3.96KB

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

9.35MB

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

8.15KB

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

7.26MB

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

2.49KB

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

4.73MB

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

3.49KB

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

23.48MB

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

8.68KB

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

3.41MB

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

78.27MB

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

6.34MB

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

4.72KB

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

14.7MB

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

11.5KB

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

4.47MB

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

1.65KB

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

4.42MB

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

14.94MB

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

12.01MB

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

4.62KB

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

4.8MB

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

4.25KB

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

24.69MB

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

7.35KB

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

14.21MB

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

6.09KB

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

11.41MB

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

6.43KB

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

4.03MB

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

3.42KB

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

5.26MB

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

3.82KB

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

9.82MB

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

6.47KB

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

21.44MB

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

16.01KB

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

10.11MB

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

7.96KB

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

13.49MB

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

5.84KB

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

24.05MB

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

8.1KB

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

2.92MB

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

1.74KB

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

5.45MB

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

3.82KB

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

78.28MB

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

78.3MB

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

7.84MB

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

6.65KB

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

29.32MB

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

17.09KB

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

37.62MB

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

25.1KB

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

37.83MB

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

8.37KB

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

22.82MB

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

5.93KB

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

186.28MB

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

21.64KB

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

43.92MB

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

15.47KB

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

24.53MB

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

24.3KB

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

14.8MB

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

14.05KB

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

5.43MB

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

4.39KB

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

12.99MB

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

15.54KB

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

38.96MB

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

33.92KB

Readme.txt

962B

[GigaCourse.com].url

49B

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