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

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

Torrent:	Udemy - Deep Learning Prerequisites Logistic Regression in Python [GC]
Description:	Udemy - Deep Learning Prerequisites Logistic Regression in Python This course is a lead-in to deep learning and neural networks - it covers a popular and fundamental technique used in machine learning, data science and statistics: logistic regression. We cover the theory from the ground up: derivation of the solution, and applications to real-world problems. We show you how one might code their own logistic regression module in Python. For more Udemy Courses: https://gigacourse.com
Downloads:	209
Category:	Other /Tutorials
Size:	1.3 GB
Show Files »	[GigaCourse.com] Udemy - Deep Learning Prerequisites Logistic Regression in Python 1. Start Here 1. Introduction and Outline.mp4 (46.9 MB) 1. Introduction and Outline.srt (5.3 KB) 2. How to Succeed in this Course.mp4 (6.4 MB) 2. How to Succeed in this Course.srt (4.0 KB) 3. Review of the classification problem.mp4 (3.0 MB) 3. Review of the classification problem.srt (2.2 KB) 4. Introduction to the E-Commerce Course Project.mp4 (14.8 MB) 4. Introduction to the E-Commerce Course Project.srt (7.6 MB) 5. Easy first quiz.html (0.1 KB) 2. Basics What is linear classification What's the relation to neural networks 1. Linear Classification.mp4 (7.6 MB) 1. Linear Classification.srt (5.2 KB) 2. Biological inspiration - the neuron.mp4 (9.4 MB) 2. Biological inspiration - the neuron.srt (4.4 KB) 3. How do we calculate the output of a neuron logistic classifier - Theory.mp4 (15.2 MB) 3. How do we calculate the output of a neuron logistic classifier - Theory.srt (80.2 MB) 4. How do we calculate the output of a neuron logistic classifier - Code.mp4 (5.8 MB) 4. How do we calculate the output of a neuron logistic classifier - Code.srt (4.5 KB) 5. Interpretation of Logistic Regression Output.mp4 (27.9 MB) 5. Interpretation of Logistic Regression Output.srt (6.4 KB) 6. E-Commerce Course Project Pre-Processing the Data.mp4 (11.2 MB) 6. E-Commerce Course Project Pre-Processing the Data.srt (5.1 KB) 7. E-Commerce Course Project Making Predictions.mp4 (5.7 MB) 7. E-Commerce Course Project Making Predictions.srt (3.0 KB) 8. Feedforward Quiz.mp4 (2.3 MB) 8. Feedforward Quiz.srt (1.7 KB) 9. Prediction Section Summary.mp4 (2.2 MB) 9. Prediction Section Summary.srt (1.5 KB) 3. Solving for the optimal weights 1. Training Section Introduction.mp4 (2.8 MB) 1. Training Section Introduction.srt (2.0 KB) 10. E-Commerce Course Project Training the Logistic Model.mp4 (17.1 MB) 10. E-Commerce Course Project Training the Logistic Model.srt (5.3 KB) 11. Training Section Summary.mp4 (3.4 MB) 11. Training Section Summary.srt (2.6 KB) 2. A closed-form solution to the Bayes classifier.mp4 (9.1 MB) 2. A closed-form solution to the Bayes classifier.srt (7.3 KB) 3. What do all these symbols mean X, Y, N, D, L, J, P(Y=1X), etc..mp4 (6.4 MB) 3. What do all these symbols mean X, Y, N, D, L, J, P(Y=1X), etc..srt (5.2 KB) 4. The cross-entropy error function - Theory.mp4 (4.5 MB) 4. The cross-entropy error function - Theory.srt (4.4 KB) 5. The cross-entropy error function - Code.mp4 (9.1 MB) 5. The cross-entropy error function - Code.srt (3.9 KB) 6. Visualizing the linear discriminant Bayes classifier Gaussian clouds.mp4 (5.3 MB) 6. Visualizing the linear discriminant Bayes classifier Gaussian clouds.srt (2.3 KB) 7. Maximizing the likelihood.mp4 (25.2 MB) 7. Maximizing the likelihood.srt (4.0 KB) 8. Updating the weights using gradient descent - Theory.mp4 (9.3 MB) 8. Updating the weights using gradient descent - Theory.srt (8.1 KB) 9. Updating the weights using gradient descent - Code.mp4 (7.3 MB) 9. Updating the weights using gradient descent - Code.srt (2.5 KB) 4. Practical concerns 1. Practical Section Introduction.mp4 (4.7 MB) 1. Practical Section Introduction.srt (3.5 KB) 10. Why Divide by Square Root of D.mp4 (23.5 MB) 10. Why Divide by Square Root of D.srt (8.7 KB) 11. Practical Section Summary.mp4 (3.4 MB) 11. Practical Section Summary.srt (78.3 MB) 2. Interpreting the Weights.mp4 (6.3 MB) 2. Interpreting the Weights.srt (4.7 KB) 3. L2 Regularization - Theory.mp4 (14.7 MB) 3. L2 Regularization - Theory.srt (11.5 KB) 4. L2 Regularization - Code.mp4 (4.5 MB) 4. L2 Regularization - Code.srt (1.6 KB) 5. L1 Regularization - Theory.mp4 (4.4 MB) 5. L1 Regularization - Theory.srt (14.9 MB) 6. L1 Regularization - Code.mp4 (12.0 MB) 6. L1 Regularization - Code.srt (4.6 KB) 7. L1 vs L2 Regularization.mp4 (4.8 MB) 7. L1 vs L2 Regularization.srt (4.3 KB) 8. The donut problem.mp4 (24.7 MB) 8. The donut problem.srt (7.4 KB) 9. The XOR problem.mp4 (14.2 MB) 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 (11.4 MB) 1. BONUS Sentiment Analysis.srt (6.4 KB) 2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 (4.0 MB) 2. BONUS Where to get Udemy coupons and FREE deep learning material.srt (3.4 KB) 3. BONUS Exercises + how to get good at this.mp4 (5.3 MB) 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) 1. Facial Expression Recognition Project Introduction.srt (6.5 KB) 2. Facial Expression Recognition Problem Description.mp4 (21.4 MB) 2. Facial Expression Recognition Problem Description.srt (16.0 KB) 3. The class imbalance problem.mp4 (10.1 MB) 3. The class imbalance problem.srt (8.0 KB) 4. Utilities walkthrough.mp4 (13.5 MB) 4. Utilities walkthrough.srt (5.8 KB) 5. Facial Expression Recognition in Code.mp4 (24.0 MB) 5. Facial Expression Recognition in Code.srt (8.1 KB) 6. Facial Expression Recognition Project Summary.mp4 (2.9 MB) 6. Facial Expression Recognition Project Summary.srt (1.7 KB) 7. Appendix FAQ 1. What is the Appendix.mp4 (5.5 MB) 1. What is the Appendix.srt (3.8 KB) 10. Proof that using Jupyter Notebook is the same as not using it.mp4 (78.3 MB) 10. Proof that using Jupyter Notebook is the same as not using it.srt (78.3 MB) 11. Python 2 vs Python 3.mp4 (7.8 MB) 11. Python 2 vs Python 3.srt (6.6 KB) 12. What order should I take your courses in (part 1).mp4 (29.3 MB) files
Added:	2020-04-29 11:03:58
Language:	English
Peers:	Seeders : 6 , Leechers : 6
Tags:	udemy course free python
Release name:	Udemy - Deep Learning Prerequisites Logistic Regression in Python [GC]
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