Tutorialsplanet NET Udemy Deep Learning Prerequisites Logistic Regression in Python

Tutorialsplanet NET Udemy Deep Learning Prerequisites Logistic Regression in Python

Name	[Tutorialsplanet.NET] Udemy - Deep Learning Prerequisites Logistic Regression in Python	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	1.3 GB
Total Files	118
Hash	36D152EDDB26EA4B81A414403DFDD8824C26557D

/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/
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/
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/
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
/
[Tutorialsplanet.NET].url	0.1 KB
Total files 118