Top Machine Learning Frameworks

Artificial Intelligence (AI), Deep learning (DL) and Machine Learning (ML) have advanced quickly over the last few years and are proven transformative engines for companies developing new technologies to get faster results and make our lives easier. The industry itself has grown rapidly and as the popularity of DL and ML continues to solidify, choosing the right framework is an important decision, and perhaps a critical one, to remaining competitive and improving business. The number of frameworks available to data scientists and developers initially increased in the early years of AI, but many have lost out to the most popular ones: TensorFlow and PyTorch. As more support has grown around these two frameworks, smaller niche frameworks and libraries have popped up that work directly with one or both of the main standouts. This article will take a look at TensorFlow and PyTorch, as well as a couple other frameworks that are still supported.