josephmisiti/awesome-machine-learning
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Add deep learning specialization; improve README links

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Signed-off-by: Marcelo Novaes <mnovaes@gmail.com>
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Marcelo Novaes 2017-08-27 18:38:42 +02:00
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README.md
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# Awesome Machine Learning [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)
A curated list of awesome machine learning frameworks, libraries and software (by language). Inspired by awesome-php.
A curated list of awesome machine learning frameworks, libraries and software (by language). Inspired by `awesome-php`.
If you want to contribute to this list (please do), send me a pull request or contact me [@josephmisiti](https://twitter.com/josephmisiti)
Also, a listed repository should be deprecated if:
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* Repository's owner explicitly say that "this library is not maintained".
* Not committed for long time (2~3 years).
For a list of free machine learning books available for download, go [here](https://github.com/josephmisiti/awesome-machine-learning/blob/master/books.md).
Further resources:
For a list of free-to-attend meetups and local events, go [here](https://github.com/josephmisiti/awesome-machine-learning/blob/master/meetups.md).
* For a list of free machine learning books available for download, go [here](https://github.com/josephmisiti/awesome-machine-learning/blob/master/books.md).
* For a list of (mostly) free machine learning courses available online, go [here](https://github.com/josephmisiti/awesome-machine-learning/blob/master/courses.md).
* For a list of blogs on data science and machine learning, go [here](https://github.com/josephmisiti/awesome-machine-learning/blob/master/blogs.md).
* For a list of free-to-attend meetups and local events, go [here](https://github.com/josephmisiti/awesome-machine-learning/blob/master/meetups.md).
## Table of Contents

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courses.md
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* [Machine Learning (Columbia University)](https://www.edx.org/course/machine-learning-columbiax-csmm-102x) - free
* [Machine Learning (Stanford University)](https://www.coursera.org/learn/machine-learning) - free
* [Neural Networks for Machine Learning (University of Toronto)](https://www.coursera.org/learn/neural-networks) - free
* [Deep Learning Specialization (by Andrew Ng, deeplearning.ai)](https://www.coursera.org/specializations/deep-learning) - Courses: I Neural Networks and Deep Learning; II Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; III Structuring Machine Learning Projects; IV Convolutional Neural Networks; V Sequence Models; Paid for grading/certification, financial aid available, free to audit
* [Machine Learning Specialization (University of Washington)](https://www.coursera.org/specializations/machine-learning) - Courses: Machine Learning Foundations: A Case Study Approach, Machine Learning: Regression, Machine Learning: Classification, Machine Learning: Clustering & Retrieval, Machine Learning: Recommender Systems & Dimensionality Reduction,Machine Learning Capstone: An Intelligent Application with Deep Learning; free
* [Machine Learning Course (2014-15 session) (by Nando de Freitas, University of Oxford)](https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/) - Lecture slides and video recordings.
* [Learning from Data (by Yaser S. Abu-Mostafa, Caltech)](http://www.work.caltech.edu/telecourse.html) - Lecture videos available