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fileUdemy-Data-Science-Super-1qHeG

Udemy Data Science Supervised chine Learning Python
  • MP401 Introduction and Review\\/001 Introduction and Outline.mp47.62MB
  • MP401 Introduction and Review\\/002 Review of Important Concepts.mp46.01MB
  • MP401 Introduction and Review\\/003 Where to get the Code and Data.mp43.86MB
  • MP401 Introduction and Review\\/004 How to Succeed in this Course.mp48.78MB
  • MP402 K-Nearest Neighbor\\/005 K-Nearest Neighbor Concepts.mp48.60MB
  • MP402 K-Nearest Neighbor\\/006 KNN in Code with MNIST.mp417.96MB
  • MP402 K-Nearest Neighbor\\/007 When KNN Can Fail.mp47.70MB
  • MP402 K-Nearest Neighbor\\/008 KNN for the XOR Problem.mp44.26MB
  • MP402 K-Nearest Neighbor\\/009 KNN for the Donut Problem.mp45.42MB
  • MP403 Naive Bayes and Bayes Classifiers\\/010 Naive Bayes.mp415.69MB
  • MP403 Naive Bayes and Bayes Classifiers\\/011 Naive Bayes Handwritten Example.mp45.83MB
  • MP403 Naive Bayes and Bayes Classifiers\\/012 Naive Bayes in Code with MNIST.mp414.43MB
  • MP403 Naive Bayes and Bayes Classifiers\\/013 Non-Naive Bayes.mp47.30MB
  • MP403 Naive Bayes and Bayes Classifiers\\/014 Bayes Classifier in Code with MNIST.mp44.44MB
  • MP403 Naive Bayes and Bayes Classifiers\\/015 Linear Discriminant Analysis LDA and Quadratic Discriminant Analysis QDA.mp410.35MB
  • MP403 Naive Bayes and Bayes Classifiers\\/016 Generative vs Discriminative Models.mp45.12MB
  • MP404 Decision Trees\\/017 Decision Tree Basics.mp48.28MB
  • MP404 Decision Trees\\/018 Infortion Entropy.mp46.99MB
  • MP404 Decision Trees\\/019 ximizing Information Gain.mp413.96MB
  • MP404 Decision Trees\\/020 Choosing the Best Split.mp46.72MB
  • MP404 Decision Trees\\/021 Decision Tree in Code.mp430.33MB
  • MP405 Perceptrons\\/022 Perceptron Concepts.mp412.22MB
  • MP405 Perceptrons\\/023 Perceptron in Code.mp413.76MB
  • MP405 Perceptrons\\/024 Perceptron for MNIST and XOR.mp48.74MB
  • MP405 Perceptrons\\/025 Perceptron Loss Function.mp46.87MB
  • MP406 Practical chine Learning\\/026 Hyperparameters and Cross-Validation.mp47.43MB
  • MP406 Practical chine Learning\\/027 Feature Extraction and Feature Selection.mp47.09MB
  • MP406 Practical chine Learning\\/028 Comparison to Deep Learning.mp48.70MB
  • MP406 Practical chine Learning\\/029 Multiclass Classification.mp45.65MB
  • MP406 Practical chine Learning\\/030 Sci-Kit Learn.mp415.81MB
  • MP406 Practical chine Learning\\/031 Regression with Sci-Kit Learn is Easy.mp410.75MB
  • MP407 Building a chine Learning Web Service\\/032 Building a Machine Learning Web Service Concepts.mp47.24MB
  • MP407 Building a chine Learning Web Service\\/033 Building a Machine Learning Web Service Code.mp411.87MB
  • MP408 Conclusion\\/034 Whats Next Support Vector chines and Ensemble Methods e.g. Random Forest.mp46.27MB
  • MP409 Appendix\\/035 How to install Numpy Scipy tplotlib and Sci-Kit Learn.mp443.92MB
  • MP409 Appendix\\/036 How to Code by Yourself part 1.mp424.53MB
  • MP409 Appendix\\/037 How to Code by Yourself part 2.mp414.80MB
  • MP409 Appendix\\/038 Where to get Udemy coupons and FREE deep learning terial.mp44.02MB
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