Udemy - Deep Learning Prerequisites Logistic Regression in Python [GC]

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Udemy - Deep Learning Prerequisites Logistic Regression in Python [GC]

Torrent Contents Size: 1.3 GB

Udemy - Deep Learning Prerequisites Logistic Regression in Python [GC]
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1. BONUS Sentiment Analysis.mp4
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11.4 MB
1. BONUS Sentiment Analysis.srt
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6.4 KB
1. Facial Expression Recognition Project Introduction.mp4
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9.8 MB
1. Facial Expression Recognition Project Introduction.srt
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6.5 KB
1. Introduction and Outline.mp4
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46.9 MB
1. Introduction and Outline.srt
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5.3 KB
1. Linear Classification.mp4
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7.6 MB
1. Linear Classification.srt
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5.2 KB
1. Practical Section Introduction.mp4
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4.7 MB
1. Practical Section Introduction.srt
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3.5 KB
1. Training Section Introduction.mp4
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2.8 MB
1. Training Section Introduction.srt
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2 KB
1. What is the Appendix.mp4
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5.5 MB
1. What is the Appendix.srt
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3.8 KB
10. E-Commerce Course Project Training the Logistic Model.mp4
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17.1 MB
10. E-Commerce Course Project Training the Logistic Model.srt
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5.3 KB
10. Proof that using Jupyter Notebook is the same as not using it.mp4
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78.3 MB
10. Proof that using Jupyter Notebook is the same as not using it.srt
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78.3 MB
10. Why Divide by Square Root of D.mp4
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23.5 MB
10. Why Divide by Square Root of D.srt
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8.7 KB
11. Practical Section Summary.mp4
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3.4 MB
11. Practical Section Summary.srt
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78.3 MB
11. Python 2 vs Python 3.mp4
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7.8 MB
11. Python 2 vs Python 3.srt
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11. Training Section Summary.mp4
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3.4 MB
11. Training Section Summary.srt
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2.6 KB
12. What order should I take your courses in (part 1).mp4
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29.3 MB
12. What order should I take your courses in (part 1).srt
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13. What order should I take your courses in (part 2).mp4
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37.6 MB
13. What order should I take your courses in (part 2).srt
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14. BONUS Where to get discount coupons and FREE deep learning material.mp4
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37.8 MB
14. BONUS Where to get discount coupons and FREE deep learning material.srt
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8.4 KB
2. A closed-form solution to the Bayes classifier.mp4
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9.1 MB
2. A closed-form solution to the Bayes classifier.srt
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7.3 KB
2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4
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4 MB
2. BONUS Where to get Udemy coupons and FREE deep learning material.srt
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3.4 KB
2. Biological inspiration - the neuron.mp4
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9.4 MB
2. Biological inspiration - the neuron.srt
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4.4 KB
2. Facial Expression Recognition Problem Description.mp4
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21.4 MB
2. Facial Expression Recognition Problem Description.srt
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16 KB
2. Gradient Descent Tutorial.mp4
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22.8 MB
2. Gradient Descent Tutorial.srt
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5.9 KB
2. How to Succeed in this Course.mp4
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6.4 MB
2. How to Succeed in this Course.srt
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4 KB
2. Interpreting the Weights.mp4
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6.3 MB
2. Interpreting the Weights.srt
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4.7 KB
3. BONUS Exercises + how to get good at this.mp4
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5.3 MB
3. BONUS Exercises + how to get good at this.srt
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3.8 KB
3. How do we calculate the output of a neuron logistic classifier - Theory.mp4
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15.2 MB
3. How do we calculate the output of a neuron logistic classifier - Theory.srt
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80.2 MB
3. L2 Regularization - Theory.mp4
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14.7 MB
3. L2 Regularization - Theory.srt
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11.5 KB
3. Review of the classification problem.mp4
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3 MB
3. Review of the classification problem.srt
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2.2 KB
3. The class imbalance problem.mp4
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10.1 MB
3. The class imbalance problem.srt
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8 KB
3. What do all these symbols mean X, Y, N, D, L, J, P(Y=1X), etc..mp4
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6.4 MB
3. What do all these symbols mean X, Y, N, D, L, J, P(Y=1X), etc..srt
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3. Windows-Focused Environment Setup 2018.mp4
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186.3 MB
3. Windows-Focused Environment Setup 2018.srt
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21.6 KB
4. How do we calculate the output of a neuron logistic classifier - Code.mp4
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5.8 MB
4. How do we calculate the output of a neuron logistic classifier - Code.srt
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4.5 KB
4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
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43.9 MB
4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt
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15.5 KB
4. Introduction to the E-Commerce Course Project.mp4
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14.8 MB
4. Introduction to the E-Commerce Course Project.srt
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7.6 MB
4. L2 Regularization - Code.mp4
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4.5 MB
4. L2 Regularization - Code.srt
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1.6 KB
4. The cross-entropy error function - Theory.mp4
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4.5 MB
4. The cross-entropy error function - Theory.srt
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4.4 KB
4. Utilities walkthrough.mp4
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13.5 MB
4. Utilities walkthrough.srt
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5.8 KB
5. Easy first quiz.html
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102.4 B
5. Facial Expression Recognition in Code.mp4
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24 MB
5. Facial Expression Recognition in Code.srt
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5. How to Code by Yourself (part 1).mp4
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24.5 MB
5. How to Code by Yourself (part 1).srt
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24.3 KB
5. Interpretation of Logistic Regression Output.mp4
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27.9 MB
5. Interpretation of Logistic Regression Output.srt
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6.4 KB
5. L1 Regularization - Theory.mp4
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4.4 MB
5. L1 Regularization - Theory.srt
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14.9 MB
5. The cross-entropy error function - Code.mp4
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9.1 MB
5. The cross-entropy error function - Code.srt
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3.9 KB
6. E-Commerce Course Project Pre-Processing the Data.mp4
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11.2 MB
6. E-Commerce Course Project Pre-Processing the Data.srt
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5.1 KB
6. Facial Expression Recognition Project Summary.mp4
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2.9 MB
6. Facial Expression Recognition Project Summary.srt
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1.7 KB
6. How to Code by Yourself (part 2).mp4
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14.8 MB
6. How to Code by Yourself (part 2).srt
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14 KB
6. L1 Regularization - Code.mp4
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12 MB
6. L1 Regularization - Code.srt
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4.6 KB
6. Visualizing the linear discriminant Bayes classifier Gaussian clouds.mp4
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5.3 MB
6. Visualizing the linear discriminant Bayes classifier Gaussian clouds.srt
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2.3 KB
7. E-Commerce Course Project Making Predictions.mp4
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5.7 MB
7. E-Commerce Course Project Making Predictions.srt
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3 KB
7. How to Uncompress a .tar.gz file.mp4
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5.4 MB
7. How to Uncompress a .tar.gz file.srt
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4.4 KB
7. L1 vs L2 Regularization.mp4
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4.8 MB
7. L1 vs L2 Regularization.srt
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4.3 KB
7. Maximizing the likelihood.mp4
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25.2 MB
7. Maximizing the likelihood.srt
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4 KB
8. Feedforward Quiz.mp4
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2.3 MB
8. Feedforward Quiz.srt
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1.7 KB
8. How to Succeed in this Course (Long Version).mp4
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13 MB
8. How to Succeed in this Course (Long Version).srt
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15.5 KB
8. The donut problem.mp4
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24.7 MB
8. The donut problem.srt
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7.4 KB
8. Updating the weights using gradient descent - Theory.mp4
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9.3 MB
8. Updating the weights using gradient descent - Theory.srt
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8.1 KB
9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4
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39 MB
9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt
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33.9 KB
9. Prediction Section Summary.mp4
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2.2 MB
9. Prediction Section Summary.srt
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1.5 KB
9. The XOR problem.mp4
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14.2 MB
9. The XOR problem.srt
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6.1 KB
9. Updating the weights using gradient descent - Code.mp4
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7.3 MB
9. Updating the weights using gradient descent - Code.srt
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2.5 KB
Readme.txt
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921.6 B
[GigaCourse.com].url
URL
0 B

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