Deep Learning Resources

Best way to learn DL from scratch in 2018

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There are more and more amazing resources that make Deep Learning more accessible than ever. A few years ago, it would be extremely hard to find a good introduction that doesn’t overwhelm you with a gigantic list of prerequisites. Now, you don’t need eleven PhD’s to get started. If you know python — you can start training your first ANNs in a matter of days, and get quite comfortable in this field in a few months.

This is a collection of the best resources that will help you get started, that assumes no prerequisites other than basic understanding of Python.

Python for Data Science and Machine Learning

If you are unsure about your python skills, I recommend getting started here. This simple introductory course will take you through all the libraries you will
need to comfortably follow any of the courses below. Use it to refresh your memory, and learn the fundamentals of Python, Jupyter, NumPy, and Matplotlib.
There are more sections in this course, but as long as you know these 4 — you’re good.

3blue1brown videos on neural networks

The best way to understand the basics of DL is to watch this extremely brilliant high-level concise overview of how ANNs work. I highly recommend you get started
here. Watch these 4 short videos, and you have a good general idea of everything you’ll need to learn in more detail using the other resources.

Grokking Deep Learning

This is a fantastic book that will teach you the fundamental principles of Deep Learning. It has very intuitive and easy to follow explanations, and doesn’t use
any libraries other than NumPy. You will gradually build up your understanding, and build all the basic algorithms you want to know, from scratch.

Deep Learning With Python

Unlike the previous book, this one doesn’t go into math and theory, instead guides you through building several practical projects with a very simple to use
DL library(keras). It’s a great way to gain practical experience in addition to the theory from the previous book. Also has no prerequisites other than python,
and makes it very easy to get started.

Fast.ai Deep Learning course (v.2)

If you’re looking for the fastest, easiest way to go from zero to training cutting edge deep learning algorithms, the best place to learn is
fast.ai.

This is a free course that teaches you deep learning using a top-down approach. You will begin by training a state of the art image classifier using only a few
lines of code in the first couple of hours, and as you follow along, the course will go more in depth explaining the theory, other algorithms, and giving you a
complete understanding of how things work.

The amount of information might be a little overwhelming at first, that’s why I recommend you to also use the books mentioned above if you get confused at any
point.

These 5 resources will be enough to take you from zero to competently training ANNs in a few months. The rest of the article is a collection of other excellent
resources that will make your journey easier.

Math Prerequisites

The easiest way to learn the math you’ll need for DL is by following Khan Academy and 3blue1brown’s courses. You won’t need to learn all of this before
other courses, but I recommend watching these videos in your free time, eventually you will find this knowledge useful. Most importantly, you will need
to know these 3 subjects: