[I didn’t know where to put this]
I need some help in getting my DL priorities straight.
I was hoping that the people on this forum might be able to give me some direction
TLDR: I’ve got a lot of goals this semester along with a lot of work. And I am unable to decide how to properly proceed with my Deep Learning journey in a way that is most highly impactful for me in future given my goals after graduation.
I am very short on time and I need to make a few key decisions regarding how best to go about: Part 1 2020, V2 Walkthroughs, Part 2 2020, The Deep Learning Book.
A little bit about me for some context: Introduction Post
https://akashpalrecha.me/about.html
The Problem:
So, this semester (3rd year) in college, I’ve got a bunch of fixed, ** have to do ** priorities:
-
Pixxel, a space-tech startup (will sell Hyperspectral Imagery of the earth commercially for the first time) where I’m working as an AI Researcher and technical team lead.
- College Math Courses, of course.
- A semester project with a professor which requires me to be familiar with the first half of FastAI’s Computational Linear Algebra Course
- A CVPR Competition Track I’m participating in with my colleague in Pixxel.
Among all of this, I want to take out as much time as possible for Part 1 2020 when it starts streaming live. Which I will, with all the discipline I have.
As of now, I’ve completed Part 1 of the course from the last 2 years along with (most of) 2019’s Part 2 and I’m deeply familiar with FastAI V1’s source code.
So I was thinking whether or not should I go through all the FastAI V2’s Walkthroughs that Jeremy has posted online. I’m concerned about the fact that since I am going to do Part 1 2020 anyway, if the material for those is heavily intersecting, it might prove counter-productive for me.
This is a concern because I’m going to be very very busy this semester in college and I want to use my time as efficiently as possible and avoid re-doing things.
(Also, Part 1 2020 will be beginning when my midsemester exams start and ending with my final examinations. That’ll make things a bit more uncomfortable than I’d like)
Also, @jeremy, is Part 2 of 2020 going to cover a lot of FastAI V2’s internals like last year? Since I’m going to be dedicatedly doing that part of the course too, I’d rather skip the Walkthroughs for now if that’s the case (I don’t want to. I really don’t want to. But I’m hard-pressed for time).
I was also hoping to comprehensively go through the Deep Learning book by Ian Goodfellow along with the FastAI courses. So, if Part 2 this year is going to discuss a lot of deep learning theory, then I’d defer reading the book for when the course comes out and would ideally read it while going through the course. I’ve coded a lot of DL models already and feel like now is the time to finally go through the theory properly.
What am I hoping to achieve: By the time Part 2 of this year ends (nearing the beginning of my 4th year), I want to be extremely well versed in both DL theory and practical applications such that I can confidently apply to and interview for even the most competitive AI positions in great companies/universities around the world.
In Summary:
- Is Part 1 2020 going to cover things similar to the walkthroughs?
- If the answer to the above is NO, then since I’m extremely short of time, should I go through the walkthroughs or will that content be covered in Part 2 of the course anyway?
- Should I read the Deep Learning book before Part 2 starts or read it along as the course proceeds?
I’d be very grategul if people around here can give their viewpoints on how I should go about things.