Chapter 16. Where to go from here: a brief guide

 

In this chapter

  • Step 1: Start learning PyTorch
  • Step 2: Start another deep learning course
  • Step 3: Grab a mathy deep learning textbook
  • Step 4: Start a blog, and teach deep learning
  • Step 5: Twitter
  • Step 6: Implement academic papers
  • Step 7: Acquire access to a GPU
  • Step 8: Get paid to practice
  • Step 9: Join an open source project
  • Step 10: Develop your local community

“Whether you believe you can do a thing or not, you are right.”

Henry Ford, automobile manufacturer

Congratulations!

If you’re reading this, you’ve made it through nearly 300 pages of deep learning

You did it! This was a lot of material. I’m proud of you, and you should be proud of yourself. Today should be a cause for celebration. At this point, you understand the basic concepts behind artificial intelligence, and should feel quite confident in your abilities to speak about them as well as your abilities to learn advanced concepts.

This last chapter includes a few short sections discussing appropriate next steps for you, especially if this is your first resource in the field of deep learning. My general assumption is that you’re interested in pursuing a career in the field or at least continuing to dabble on the side, and I hope my general comments will help guide you in the right direction (although they’re only very general guidelines that may or may not directly apply to you).

Step 1: Start learning PyTorch

The deep learning framework you made most closely resembles PyTorch

Step 2: Start another deep learning course

Step 3: Grab a mathy deep learning textbook

Step 4: Start a blog, and teach deep learning

Step 5: Twitter

Step 6: Implement academic papers

Step 7: Acquire access to a GPU (or many)

Step 8: Get paid to practice

Step 9: Join an open source project

Step 10: Develop your local community