Learning Path to Deep Learning and Machine Learning

Courses and books:

  • Machine Learning by Stanford University: This is a must for those of you with no background about Machine Learning and Data Science. It is taught by Andrew Ng, the person responsible for the deeplearning.ai initiative that a month ago started offering a set of courses to teach everyone deep learning from scratch (Check out these deeplearning.ai courses as they may be a great fit for you too).
  • Fast AI Deep Learning Course: Equivalent to the deeplearning.ai courses. The main difference between them is that the deeplearning.ai degree is built from down to top (DL internals to practical DL), while fast.ai follows a top to down approach (practical matters to DL internals)
  • CS231n: Convolutional Neural Networks for Visual Recognition 2017 (2016): If what you like is computer vision this is also a must. It will give you a great background to prepare yourself for the research field of computer vision.
  • Deep Learning by Google: This is one of those courses I tried to start several times failing in the attempt. It gives a pretty nice intro about Deep Learning. However, the lectures feel quite boring and I didn’t feel I was learning that much.
  • CS224d: Deep Learning for Natural Language Processing: Enjoyable course to approach if what you are interested in is Natural Learning Processing. Right now I am working on this field and let my assure you that it will give you all that you need to start a career in the NLP world.

And what about the practice?

  • Kaggle account. If you are wondering what Kaggle is I think the best way to understand it is sharing how they define themselves in their website “The best place to explore data science results and share your own work”. Sounds great right?




Research at Protocol Labs | Avid reader seeking for constant innovation. [https://twitter.com/adlrocha] [https://adlrocha.substack.com/subscribe]

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Alfonso de la Rocha

Alfonso de la Rocha

Research at Protocol Labs | Avid reader seeking for constant innovation. [https://twitter.com/adlrocha] [https://adlrocha.substack.com/subscribe]

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