Software 2.0 is a completely different paradigm. A different way of thinking, organizing information, and building.
Classical programming is about writing rules and applying them to data to produce answers.
But, sometimes, those rules aren't obvious and we can't write them.
Machine Learning breaks through that wall: you don't write the rules; you learn them from data.
Software 2.0 is about analyzing data, finding patterns, learning basic principles, and composing and generalizing these to solve novel problems.
This is so much more powerful than everything we've seen before.
There's still a ton of work to get there, but this is not a hypothetical future anymore. Look at every large company around you and you'll realize they are all in this with both feet.
Software 2.0 is happening, and the only question that remains is how each of us will adapt to take advantage of it.
Software engineers make great machine learning engineers.
A popular advice is to tell people to learn math if they want to succeed with machine learning.
I'd say you'll be better off focusing on software engineering.
This is the best introduction to Statistics and Probabilities I've read.
"The Cartoon Guide to Statistics" is anything but boring.
It's easy to read and fun. It's accessible to anyone regardless of their background.
Every math book should be like this.
https://t.co/IXhLgrca6z
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