Why You Should NOT Learn Machine Learning!

Why You Should NOT Learn Machine Learning!



Everyone tells you why you should be learning machine learning. It is the next ‘big thing’ after all. But in this video I’m going to be telling you why you should NOT learn machine learning.

There are many reasons for not starting machine learning. Some of these are:
1. Don’t get into ML just because it is popular. Basically do not FOMO into it.
2. Machine learning is a huge field, there are so many things to do. You might start it but eventually give up because you don’t know what exactly you want to build using ML/AI.
3. Just because you saw people getting paid more for machine learning jobs doesn’t mean you should start it. As you can still polish your skills in other computer science related fields.

Even though I mention why you should not be get into machine learning, this doesn’t mean that you should not at least give it a go. This video is only made for some people who want to get into ML/AI without having any major goal.

Let me know what you think about this in the comment section below.

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C Programming for Machine Learning (LIVE)

C Programming for Machine Learning (LIVE)



The ability to write implementations of machine learning algorithms in pure C allows developers to very efficiently manage memory allocation, concurrency, and control flow. That means fast implementations that can outperform preexisting models in other languages, including even (gasp) Python. It’s a useful skill to know and in this live stream I’ll use C and C-based Python tools like Cython + spaCy to develop some really fast natural language processing algorithms for text data. We’ll be able to tokenize, tag, normalize, vectorize, and dependency parse articles of text to derive valuable insights. No installation necessary, we’ll do this together using Google Colab in the browser. Join me, there’s a lot to cover here!

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