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[FreeTutorials.Us] data-science-logistic-regression-in-python

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424.52MB

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2019-08-01

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FreeTutorials Us data science logistic regression in python

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File Name

Size

01 Start Here/quizzes/001 Easy first quiz.html

2.43KB

01 Start Here/001 Introduction and Outline.mp4

7.52MB

01 Start Here/002 How to Succeed in this Course.mp4

8.78MB

01 Start Here/003 Review of the classification problem.mp4

2.97MB

01 Start Here/004 Introduction to the E-Commerce Course Project.mp4

14.79MB

02 Basics What is linear classification Whats the relation to neural networks/005 Linear Classification.mp4

7.54MB

02 Basics What is linear classification Whats the relation to neural networks/006 Biological inspiration - the neuron.mp4

4.17MB

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

7.48MB

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

5.82MB

02 Basics What is linear classification Whats the relation to neural networks/009 E-Commerce Course Project Pre-Processing the Data.mp4

11.16MB

02 Basics What is linear classification Whats the relation to neural networks/010 E-Commerce Course Project Making Predictions.mp4

5.7MB

03 Solving for the optimal weights/011 A closed-form solution to the Bayes classifier.mp4

9.99MB

03 Solving for the optimal weights/012 What do all these symbols mean X Y N D L J PY1X etc..mp4

6.36MB

03 Solving for the optimal weights/013 The cross-entropy error function - Theory.mp4

4.49MB

03 Solving for the optimal weights/014 The cross-entropy error function - Code.mp4

9.1MB

03 Solving for the optimal weights/015 Visualizing the linear discriminant Bayes classifier Gaussian clouds.mp4

5.27MB

03 Solving for the optimal weights/016 Maximizing the likelihood.mp4

12.67MB

03 Solving for the optimal weights/017 Updating the weights using gradient descent - Theory.mp4

9.35MB

03 Solving for the optimal weights/018 Updating the weights using gradient descent - Code.mp4

7.25MB

03 Solving for the optimal weights/019 E-Commerce Course Project Training the Logistic Model.mp4

17.06MB

04 Practical concerns/020 Interpreting the Weights.mp4

6.34MB

04 Practical concerns/021 L2 Regularization - Theory.mp4

14.7MB

04 Practical concerns/022 L2 Regularization - Code.mp4

4.46MB

04 Practical concerns/023 L1 Regularization - Theory.mp4

4.42MB

04 Practical concerns/024 L1 Regularization - Code.mp4

12.01MB

04 Practical concerns/025 L1 vs L2 Regularization.mp4

4.8MB

04 Practical concerns/026 The donut problem.mp4

24.68MB

04 Practical concerns/027 The XOR problem.mp4

14.2MB

05 Checkpoint and applications How to make sure you know your stuff/028 BONUS Sentiment Analysis.mp4

11.4MB

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

4.02MB

05 Checkpoint and applications How to make sure you know your stuff/030 BONUS Exercises how to get good at this.mp4

5.26MB

06 Project Facial Expression Recognition/031 Facial Expression Recognition Problem Description.mp4

21.43MB

06 Project Facial Expression Recognition/032 The class imbalance problem.mp4

10.11MB

06 Project Facial Expression Recognition/033 Utilities walkthrough.mp4

13.48MB

06 Project Facial Expression Recognition/034 Facial Expression Recognition in Code.mp4

24.04MB

07 Appendix/035 Gradient Descent Tutorial.mp4

8.43MB

07 Appendix/036 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4

43.92MB

07 Appendix/037 How to Code by Yourself part 1.mp4

24.53MB

07 Appendix/038 How to Code by Yourself part 2.mp4

14.8MB

[FreeTutorials.Us].txt

75B

Freetutorials.Us.url

119B

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