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- 07 Appendix/036 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 46.0 MB
- 04 Practical concerns/026 The donut problem.mp4 25.9 MB
- 07 Appendix/037 How to Code by Yourself part 1.mp4 25.7 MB
- 06 Project Facial Expression Recognition/034 Facial Expression Recognition in Code.mp4 25.2 MB
- 06 Project Facial Expression Recognition/031 Facial Expression Recognition Problem Description.mp4 22.5 MB
- 03 Solving for the optimal weights/019 E-Commerce Course Project Training the Logistic Model.mp4 17.9 MB
- 07 Appendix/038 How to Code by Yourself part 2.mp4 15.5 MB
- 01 Start Here/004 Introduction to the E-Commerce Course Project.mp4 15.5 MB
- 04 Practical concerns/021 L2 Regularization - Theory.mp4 15.4 MB
- 04 Practical concerns/027 The XOR problem.mp4 14.9 MB
- 06 Project Facial Expression Recognition/033 Utilities walkthrough.mp4 14.1 MB
- 03 Solving for the optimal weights/016 Maximizing the likelihood.mp4 13.3 MB
- 04 Practical concerns/024 L1 Regularization - Code.mp4 12.6 MB
- 05 Checkpoint and applications How to make sure you know your stuff/028 BONUS Sentiment Analysis.mp4 12.0 MB
- 02 Basics What is linear classification Whats the relation to neural networks/009 E-Commerce Course Project Pre-Processing the Data.mp4 11.7 MB
- 06 Project Facial Expression Recognition/032 The class imbalance problem.mp4 10.6 MB
- 03 Solving for the optimal weights/011 A closed-form solution to the Bayes classifier.mp4 10.5 MB
- 03 Solving for the optimal weights/017 Updating the weights using gradient descent - Theory.mp4 9.8 MB
- 03 Solving for the optimal weights/014 The cross-entropy error function - Code.mp4 9.5 MB
- 01 Start Here/002 How to Succeed in this Course.mp4 9.2 MB
- 07 Appendix/035 Gradient Descent Tutorial.mp4 8.8 MB
- 02 Basics What is linear classification Whats the relation to neural networks/005 Linear Classification.mp4 7.9 MB
- 01 Start Here/001 Introduction and Outline.mp4 7.9 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 7.8 MB
- 03 Solving for the optimal weights/018 Updating the weights using gradient descent - Code.mp4 7.6 MB
- 03 Solving for the optimal weights/012 What do all these symbols mean X Y N D L J PY1X etc..mp4 6.7 MB
- 04 Practical concerns/020 Interpreting the Weights.mp4 6.6 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 6.1 MB
- 02 Basics What is linear classification Whats the relation to neural networks/010 E-Commerce Course Project Making Predictions.mp4 6.0 MB
- 03 Solving for the optimal weights/015 Visualizing the linear discriminant Bayes classifier Gaussian clouds.mp4 5.5 MB
- 05 Checkpoint and applications How to make sure you know your stuff/030 BONUS Exercises how to get good at this.mp4 5.5 MB
- 04 Practical concerns/025 L1 vs L2 Regularization.mp4 5.0 MB
- 03 Solving for the optimal weights/013 The cross-entropy error function - Theory.mp4 4.7 MB
- 04 Practical concerns/022 L2 Regularization - Code.mp4 4.7 MB
- 04 Practical concerns/023 L1 Regularization - Theory.mp4 4.6 MB
- 02 Basics What is linear classification Whats the relation to neural networks/006 Biological inspiration - the neuron.mp4 4.4 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 4.2 MB
- 01 Start Here/003 Review of the classification problem.mp4 3.1 MB
- 01 Start Here/quizzes/001 Easy first quiz.html 2.5 kB
- udemycoursedownloader.com.url 132 Bytes
- Udemy Course downloader.txt 94 Bytes
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