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[UdemyCourseDownloader] Deep Learning Prerequisites Logistic Regression in Python
magnet:?xt=urn:btih:795d8ae27fbab24eb25a108635fdcaa26138177c&dn=[UdemyCourseDownloader] Deep Learning Prerequisites Logistic Regression in Python
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文件列表详情
795d8ae27fbab24eb25a108635fdcaa26138177c
infohash:
38
文件数量
424.52 MB
文件大小
2019-3-19 17:28
创建日期
2024-11-26 09:36
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相关分词
UdemyCourseDownloader
Deep
Learning
Prerequisites
Logistic
Regression
in
Python
07 Appendix/036 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 43.92 MB
01 Start Here/001 Introduction and Outline.mp4 7.52 MB
01 Start Here/002 How to Succeed in this Course.mp4 8.78 MB
01 Start Here/003 Review of the classification problem.mp4 2.97 MB
01 Start Here/004 Introduction to the E-Commerce Course Project.mp4 14.79 MB
02 Basics What is linear classification Whats the relation to neural networks/005 Linear Classification.mp4 7.54 MB
02 Basics What is linear classification Whats the relation to neural networks/006 Biological inspiration - the neuron.mp4 4.17 MB
02 Basics What is linear classification Whats the relation to neural networks/007 How do we calculate the output of a neuron logistic classifier - Theory.mp4 7.48 MB
02 Basics What is linear classification Whats the relation to neural networks/008 How do we calculate the output of a neuron logistic classifier - Code.mp4 5.82 MB
02 Basics What is linear classification Whats the relation to neural networks/009 E-Commerce Course Project Pre-Processing the Data.mp4 11.16 MB
02 Basics What is linear classification Whats the relation to neural networks/010 E-Commerce Course Project Making Predictions.mp4 5.7 MB
03 Solving for the optimal weights/011 A closed-form solution to the Bayes classifier.mp4 9.99 MB
03 Solving for the optimal weights/012 What do all these symbols mean X Y N D L J PY1X etc..mp4 6.36 MB
03 Solving for the optimal weights/013 The cross-entropy error function - Theory.mp4 4.49 MB
03 Solving for the optimal weights/014 The cross-entropy error function - Code.mp4 9.1 MB
03 Solving for the optimal weights/015 Visualizing the linear discriminant Bayes classifier Gaussian clouds.mp4 5.27 MB
03 Solving for the optimal weights/016 Maximizing the likelihood.mp4 12.67 MB
03 Solving for the optimal weights/017 Updating the weights using gradient descent - Theory.mp4 9.35 MB
03 Solving for the optimal weights/018 Updating the weights using gradient descent - Code.mp4 7.25 MB
03 Solving for the optimal weights/019 E-Commerce Course Project Training the Logistic Model.mp4 17.06 MB
04 Practical concerns/020 Interpreting the Weights.mp4 6.34 MB
04 Practical concerns/021 L2 Regularization - Theory.mp4 14.7 MB
04 Practical concerns/022 L2 Regularization - Code.mp4 4.46 MB
04 Practical concerns/023 L1 Regularization - Theory.mp4 4.42 MB
04 Practical concerns/024 L1 Regularization - Code.mp4 12.01 MB
04 Practical concerns/025 L1 vs L2 Regularization.mp4 4.8 MB
04 Practical concerns/026 The donut problem.mp4 24.68 MB
04 Practical concerns/027 The XOR problem.mp4 14.2 MB
05 Checkpoint and applications How to make sure you know your stuff/028 BONUS Sentiment Analysis.mp4 11.4 MB
05 Checkpoint and applications How to make sure you know your stuff/029 BONUS Where to get Udemy coupons and FREE deep learning material.mp4 4.02 MB
05 Checkpoint and applications How to make sure you know your stuff/030 BONUS Exercises how to get good at this.mp4 5.26 MB
06 Project Facial Expression Recognition/031 Facial Expression Recognition Problem Description.mp4 21.43 MB
06 Project Facial Expression Recognition/032 The class imbalance problem.mp4 10.11 MB
06 Project Facial Expression Recognition/033 Utilities walkthrough.mp4 13.48 MB
06 Project Facial Expression Recognition/034 Facial Expression Recognition in Code.mp4 24.04 MB
07 Appendix/035 Gradient Descent Tutorial.mp4 8.43 MB
07 Appendix/037 How to Code by Yourself part 1.mp4 24.53 MB
07 Appendix/038 How to Code by Yourself part 2.mp4 14.8 MB
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