The first chapter and the first week of the fastai course

My background is in Management and Marketing; I’m not and have never been a tech guy.
No, I’m not planning to change my career dramatically and become an engineer (but who knows what is in the future). The thing is that I believe that algorithms are everywhere; even people are biological algorithms with their habits.
I started learning deep learning because I want to bring more of this technology into the marketing field, starting with the field of events marketing, which I am currently involved in.

I’ve tried to learn Machine Learning and Python on other different platforms, but what I liked in the unpack fastai course is that:
1. You need to deposit some money as a gesture of your commitment. In my case, it was 1000 RMB. Money can be returned only after I finish all of the first 6 weeks (the whole course should be 6 months If I’m not mistaken). If I stop following the deadlines and weekly meetings, then my money 1k RMB is gone. That’s a huge motivation, even though the amount of money is not that much for the deep learning course.

2. There are people, teachers waiting for your homework to be done on time so that you can follow on the further topics. It’s not like the courses that can fit your schedule, and you can always postpone your homework, as you’ve got all of the other stuff to do (we are always busy, right?). You feel some kind of responsibility, as those teachers spend their time voluntarily. This is a non-profit project. The feeling of responsibility makes me writing this text at almost 1 AM lol.

There are a lot of teaching ML courses on the web right now, but the 2 facts written above were enough for me to give it a try with the fastai.

Before you start, you need to buy a book called “Deep learning for Coders with fastai & PyTorch.”
Then you need to get comfortable with the Jupyter notebook on Colab or Gradient (which I found more user-friendly after my first day) and watch the first video lesson.

Basically, within the first lesson, you learn more about the application and main aspects of ML and DL in the real world; what software we are going to use; jargon that needs to be learned; AND we run our first model.
Yes, you are not building it from scratch; you run a code that the authors already placed in the notebook. But I was excited so much, like a kid waiting for Santa, to import a library, run some codes, upload a photo of a cat, and then the output determines whether it was a cat or not. So tech guy or more experienced one would think — “WTF? Are you really excited about this?” But for me, it was a feeling that I created something.

Frankly speaking, there was not much extremely new theoretical information for me (as I was reading above ML and AI before), but running the model that can filter cats and dogs was fun.

I don’t set any super high expectations, but I can’t wait till the next lesson.

P.S. we have a great community in a WeChat group where guys learn together and help each other.