Machine learning

Courses

• • Machine Learning - Stanford (one of the best, probably; start with this one)

    • Download lectures and slides: https://class.coursera.org/ml-003/lecture

  • Learning from Data - Caltech (very good one, too, from what I hear)

    • Videos of the course: https://www.youtube.com/playlist?list=PLD63A284B7615313A

  • Neural Networks for Machine Learning - Toronto (very good one, too, from what I hear)

• Intro to Artificial Intelligence

• Deep Learning - Google

• Mining Massive Datasets - Stanford

• Machine Learning - Carnegie Mellon

• Artificial Intelligence Planning - Edinburgh

• Computational Neuroscience - Washington

• Natural Language Processing - Columbia

• Intro to Python for Data Science

  • Scientific Python lectures (very good introduction in Python and the scientific libraries used in machine learning and data analysis)

• Introduction to Data Science - Washington

  • Introduction to Artificial Intelligence 

Videos

• SciPy 2015: Scientific Computing with Python Conference 

• Harvard CS-109

Articles / Blogs

• http://www.kdnuggets.com/2016/03/data-science-puzzle-explained.html

• http://www.kdnuggets.com/2015/11/seven-steps-machine-learning-python.html

• https://medium.com/learning-new-stuff/machine-learning-in-a-week-a0da25d59850#.6e9bt0gzs

• http://www.wildml.com/2015/09/implementing-a-neural-network-from-scratch/

• http://colah.github.io/

• http://iamtrask.github.io/2015/07/12/basic-python-network

• http://www.shivonzilis.com/machineintelligence

• https://github.com/Quartz/bad-data-guide

• http://fossbytes.com/become-data-scientist-simple-steps-infographic/

• http://www.kdnuggets.com/2015/09/free-data-science-books.html

• http://www.kdnuggets.com/2015/10/5-steps-learn-data-science.html

• http://www.kdnuggets.com/2016/01/20-questions-to-detect-fake-data-scientists.html

• http://www.kdnuggets.com/2016/02/21-data-science-interview-questions-answers.html

• http://scott.fortmann-roe.com/docs/BiasVariance.html

• http://scikit-learn.org/stable/tutorial/index.html

• http://www.lauradhamilton.com/machine-learning-algorithm-cheat-sheet

• https://github.com/rcompton/ml_cheat_sheet

• http://www.kdnuggets.com/2016/03/top-10-data-science-github.html

• http://www.kdnuggets.com/2016/03/must-know-tips-deep-learning-part-1.html

• http://www.simplilearn.com/resources-to-learn-data-science-online-article

Tools / Resources

• http://scikit-learn.org

• http://mldata.org

• https://www.quandl.com/

• https://www.tensorflow.org/

• https://www.kaggle.com/

• http://conceptnet5.media.mit.edu/

• http://www.datascienceontology.com/

• http://deeplearning.net/

• http://www.kdnuggets.com/

  • http://www.deeplearningbook.org/

• https://sites.google.com/site/predictingstockmovement/

• http://datasciencemasters.org/

• https://github.com/donnemartin/data-science-ipython-notebooks

  • https://www.springboard.com/blog/data-science-interview-questions/

Images

Books

• http://neuralnetworksanddeeplearning.com/index.html