Building AI - Tools of the Trade
This post is about the tricks of the trade. The stuff you need to learn in order to build meaningful AI projects. While there might be a lot of resources out there, which is the case with any technology, I intend to enlist the prominent resources that can help you build great AI projects!
Programming Languages — Python preferred
Projects and Frameworks— Tensor Flow by Google is the most popular out there. But even Scikit Learn is not a bad choice which is the second most popular choice going by the git repo stars.
Scaling and Server Side Implementation — Simply knowing how to build a smart algorithm with a cool application is not enough. When it comes to data and computationally intensive tasks like Machine Learning, it is equally important to know how to implement these systems at scale. This is where stuff like Apache Spark comes in. The following courses by Udacity are an extremely great open resource to learn about this.
If you’ve learnt so far, you might as well and go work for Google and be a millionaire. But if you’re like me, and are not too big a fan of Interviewing, go ahead, build that AI to conquer the world.
Post Script:- I’ve recently been intrigued by the possibility of Implementing AI Algorithms on Mobiles, with the processing power of these palm based devices reaching new heights every day. In that aspect, checkout Apple’s Metal Framework, it’s great to implement any computationally heavy task! Who knows, this might be the next startup gold out there!
