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filedata-science-logistic-re-1BUyF

science logistic regression python
  • MP401 Start Here\\/001 Introduction and Outline.mp47.52MB
  • MP401 Start Here\\/002 How to Succeed in this Course.mp48.78MB
  • MP401 Start Here\\/003 Review of the classification problem.mp42.97MB
  • MP401 Start Here\\/004 Introduction to the E-Commerce Course Project.mp414.79MB
  • MP402 Basics What is linear classification Whats the relation to neural networks\\/005 Linear Classification.mp47.54MB
  • MP402 Basics What is linear classification Whats the relation to neural networks\\/006 Biological inspiration - the neuron.mp44.17MB
  • MP402 Basics What is linear classification Whats the relation to neural networks\\/007 How do we calculate the output of a neuron logistic classifier - Theory.mp47.48MB
  • MP402 Basics What is linear classification Whats the relation to neural networks\\/008 How do we calculate the output of a neuron logistic classifier - Code.mp45.82MB
  • MP402 Basics What is linear classification Whats the relation to neural networks\\/009 E-Commerce Course Project Pre-Processing the Data.mp411.16MB
  • MP402 Basics What is linear classification Whats the relation to neural networks\\/010 E-Commerce Course Project king Predictions.mp45.70MB
  • MP403 Solving for the optil weights\\/011 A closed-form solution to the Bayes classifier.mp49.99MB
  • MP403 Solving for the optil weights\\/012 What do all these symbols mean X Y N D L J PY1X etc..mp46.36MB
  • MP403 Solving for the optil weights\\/013 The cross-entropy error function - Theory.mp44.49MB
  • MP403 Solving for the optil weights\\/014 The cross-entropy error function - Code.mp49.10MB
  • MP403 Solving for the optil weights\\/015 Visualizing the linear discriminant Bayes classifier Gaussian clouds.mp45.27MB
  • MP403 Solving for the optil weights\\/016 Maximizing the likelihood.mp412.67MB
  • MP403 Solving for the optil weights\\/017 Updating the weights using gradient descent - Theory.mp49.35MB
  • MP403 Solving for the optil weights\\/018 Updating the weights using gradient descent - Code.mp47.25MB
  • MP403 Solving for the optil weights\\/019 E-Commerce Course Project Training the Logistic Model.mp417.06MB
  • MP404 Practical concerns\\/020 Interpreting the Weights.mp46.34MB
  • MP404 Practical concerns\\/021 L2 Regularization - Theory.mp414.70MB
  • MP404 Practical concerns\\/022 L2 Regularization - Code.mp44.46MB
  • MP404 Practical concerns\\/023 L1 Regularization - Theory.mp44.42MB
  • MP404 Practical concerns\\/024 L1 Regularization - Code.mp412.01MB
  • MP404 Practical concerns\\/025 L1 vs L2 Regularization.mp44.80MB
  • MP404 Practical concerns\\/026 The donut problem.mp424.68MB
  • MP404 Practical concerns\\/027 The XOR problem.mp414.20MB
  • MP405 Checkpoint and applications How to ke sure you know your stuff\\/028 BONUS Sentiment Analysis.mp411.40MB
  • MP405 Checkpoint and applications How to ke sure you know your stuff\\/029 BONUS Where to get Udemy coupons and FREE deep learning material.mp44.02MB
  • MP405 Checkpoint and applications How to ke sure you know your stuff\\/030 BONUS Exercises how to get good at this.mp45.26MB
  • MP406 Project Facial ex<x>pression Recognition\\/031 Facial ex<x>pression Recognition Problem Desc<x>ription.mp421.43MB
  • MP406 Project Facial ex<x>pression Recognition\\/032 The class imbalance problem.mp410.11MB
  • MP406 Project Facial ex<x>pression Recognition\\/033 Utilities walkthrough.mp413.48MB
  • MP406 Project Facial ex<x>pression Recognition\\/034 Facial ex<x>pression Recognition in Code.mp424.04MB
  • MP407 Appendix\\/035 Gradient Descent Tutorial.mp48.43MB
  • MP407 Appendix\\/036 How to install Numpy Scipy tplotlib Pandas IPython Theano and TensorFlow.mp443.92MB
  • MP407 Appendix\\/037 How to Code by Yourself part 1.mp424.53MB
  • MP407 Appendix\\/038 How to Code by Yourself part 2.mp414.80MB
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