Here’s an interesting analyis from CodeMentor as to why Python has become the language of choice for AI and machine learning.

  • It offers an option to choose either to use OOPs or scripting.
  • There’s also no need to recompile the source code, developers can implement any changes and quickly see the results.
  • Programmers can combine Python and other languages to reach their goals.

Python has quickly grown to be the de facto language for AI and a leading language of Data Science. Its support is so widespread, however, that developers have a choice of a wide array of open source libraries. Here’s a great round up of 24 of the best.

In fact, there are so many Python libraries out there that it can become overwhelming to keep abreast of what’s out there. That’s why I decided to take away that pain and compile this list of 24 awesome Python libraries covering the end-to-end data science lifecycle.

Generative models, commonly referred to as GANs, are a family of AI architectures whose aim is to create data samples from scratch. They work by capturing the data distributions of the type of things we want to generate.

Here’s an interesting read on the topic.

These kind of models are being heavily researched, and there is a huge amount of hype around them. Just look at the chart that shows the numbers of papers published in the field over the past few years: