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Recently I have bought the book "Deep Learning with Python"[1], and I can't recommend it enough. Very gentle introduction into deep learning, through creating s

by rayalez 10y ago

Recently I have bought the book "Deep Learning with Python"[1], and I can't recommend it enough. Very gentle introduction into deep learning, through creating several practical projects. If you know the basics of ML - you should get it, it's amazing. To learn the basics of ML, you can check out the awesome tuts+ course[2]. Also I wrote an article [3] with the collection of the best free resources, I think you'll find it useful. [1] https://machinelearningmastery.com/deep-learning-with-python/ https://machinelearningmastery.com/deep-learning-with-python... [2] http://code.tutsplus.com/courses/machine-learning-distilled http://code.tutsplus.com/courses/machine-learning-distilled [3] https://medium.com/@rayalez/list-of-the-best-resources-to-learn-the-foundations-of-artificial-intelligence-934dbce5939 https://medium.com/@rayalez/list-of-the-best-resources-to-le...

zxcvvcxz 10y ago
This first book doesn't seem great. > For example, a common response to the question “how do I get started in deep learning” might be: > Develop a strong grounding in statistics, probability, linear algebra, multivariate statistics and calculus. > Develop a deep knowledge of modern machine learning algorithms and techniques. > Study and become one with the mathematical theory of each deep learning algorithm and a bunch of related techniques for using them. > Oh and if there is time find a library and start applying deep learning to your problem. > It could take a decade or more to follow this advice and that would be a decade delay that you cannot afford. Those topics are deeply important if you want to be anything more than a coder monkey, and with a decent undergrad education under one's belt (STEM-related) and half a year of dedicated part-time study, they could get up to speed in many - if not all - of those topics. But I guess whatever sells the easiest, a la "Get Rich (Smart) Quick".

by rayalez 10y ago

zxcvvcxz 10y ago

This first book doesn't seem great. > For example, a common response to the question “how do I get started in deep learning” might be: > Develop a strong grounding in statistics, probability, linear algebra, multivariate statistics and calculus. > Develop a deep knowledge of modern machine learning algorithms and techniques. > Study and become one with the mathematical theory of each deep learning algorithm and a bunch of related techniques for using them. > Oh and if there is time find a library and start applying deep learning to your problem. > It could take a decade or more to follow this advice and that would be a decade delay that you cannot afford. Those topics are deeply important if you want to be anything more than a coder monkey, and with a decent undergrad education under one's belt (STEM-related) and half a year of dedicated part-time study, they could get up to speed in many - if not all - of those topics. But I guess whatever sells the easiest, a la "Get Rich (Smart) Quick".