Machine Learning cơ bản

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• https://github.com/tpn/pdfs/blob/master/The%20Elements%20of%20Statistical%20Learning%20-%20Data%20Mining%2C%20Inference%20and%20Prediction%20-%202nd%20Edition%20(ESLII_print4).pdf
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• https://stanford.edu/~boyd/cvxbook/
• https://www.coursera.org/learn/machine-learning?utm_source=gg&utm_medium=sem&campaignid=693373197&adgroupid=36745103515&device=c&keyword=machine%20learning%20andrew%20ng&matchtype=e&network=g&devicemodel=&adpostion=1t1&creativeid=156061453588&hide_mobile_promo&gclid=Cj0KEQjwt6fHBRDtm9O8xPPHq4gBEiQAdxotvNEC6uHwKB5Ik_W87b9mo-zTkmj9ietB4sI8-WWmc5UaAi6a8P8HAQ
• http://web.stanford.edu/class/cs224n/
• http://cs231n.stanford.edu/
• http://web.stanford.edu/class/cs246/
• http://web.stanford.edu/class/cs20si/syllabus.html
• https://www.edx.org/course/introduction-computer-science-mitx-6-00-1x-10
• https://github.com/ZuzooVn/machine-learning-for-software-engineers
• http://thepresentwriter.com/chung-toi-da-apply-va-hoc-tien-si-nhu-the-nao-phan-1/
• http://thepresentwriter.com/chung-toi-da-apply-va-hoc-tien-si-nhu-the-nao-phan-2/
• http://machinelearningmastery.com/inspirational-applications-deep-learning/
• https://ccrma.stanford.edu/~dattorro/matrixcalc.pdf
• https://github.com/aymericdamien/TensorFlow-Examples
• https://www.forbes.com/sites/quora/2017/04/05/eight-easy-steps-to-get-started-learning-artificial-intelligence/#53c29fa5b117
• https://adeshpande3.github.io/adeshpande3.github.io/The-9-Deep-Learning-Papers-You-Need-To-Know-About.html