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This repository contains Python code for a selection of tables, figures and LAB sections from the book 'An Introduction to Statistical Learning with Applications in R' by James, Witten, Hastie, Tibshirani (2013). 2018-01-15: Minor updates to the repository due to changes/deprecations in several packages. The notebooks have been tested with these package versions. Thanks @lincolnfrias and @telescopeuser.

machine-learning predictive-modeling islr statistical-learningJupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"

jupyter-notebook machine-learning book books probability probability-theory statistics statistics-course statistical-analysis statistical-learning statistical-testsThis Node.js / io.js module provides access to the H2O JVM (and extensions thereof), its objects, its machine-learning algorithms, and modeling support (basic munging and feature generation) capabilities. It is designed to bring H2O to a wider audience of data and machine learning devotees that work exclusively with Javascript, for building machine learning applications or doing data munging in a fast, scalable environment without any extra mental anguish about threads and parallelism.

machine-learning predictive-analytics predictive-modeling data-mining computational-statistics statistics statistical-learning clustering classification regression deep-learningD-Lab's Machine Learning Working Group at UC Berkeley

machine-learning statistical-learning dlab ucberkeley李航《统计学习方法》笔记和 Python 实现（不基于任何代数运算库）。

machine-learning notes statistical-learningISLR is a very comprehensive notebook for understanding the basic statistical learning. However, all the sample code and exercises are based on R. Recently, I'd like to reinforce my foundation in related statistics field, therefore, I will go through the entire book with my favorite programming language Python. All the data files are converted to a format that can be handled directly by Python or popular Python packages.

statistical-learning data-science machine-learningThe GDLibrary is a pure-Matlab library of a collection of unconstrained optimization algorithms. This solves an unconstrained minimization problem of the form, min f(x). Note that the SGDLibrary internally contains this GDLibrary.

optimization optimization-algorithms machine-learning machine-learning-algorithms big-data gradient-descent gradient logistic-regression newton linear-regression svm lasso matrix-completion rosenbrock-problem softmax-regression multinomial-regression statistical-learning classificationLecture Slides for Introduction to Data Science

data-science statistical-learningA guide to using SuperLearner for prediction. Also many Coursera offerings and other online classes.

superlearner cross-validation statistical-learning ensembles tmle targeted-learningThe Elements of Statistical Learning (ESL)的中文翻译、代码实现及其习题解答。

esl statistical-learning esl-cn r julia cppThis repository contains the H2O presentation for Trevor Hastie and Rob Tibshirani's Statistical Learning and Data Mining IV course in Washington, DC on October 19, 2016.

statistical-learning deep-learning tutorial h2o machine-learning r autoencoderThis package relies on primitives defined in the JuliaML ecosystem to implement high-performance algorithms for linear models which often produce sparsity in the coefficients.

statistical-models regularization julia statistical-learning linear-models sparse-regressionLearn Deep Learning The Hard Way. It is a set of small projects on Deep Learning.

deep-learning statistical-learningWidely used and useful papers related to machine learning and deep learning

deep-learning machine-learning machine-learning-algorithms artificial-intelligence neural-network paper literature-review learning-theory reinforcement-learning statistical-learning data-mining
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