The most popular machine learning library in the world right now is Google’s tensorflow.
Pretty much every single Google product uses machine learning in some way whether it’s image search, image captioning, translation, recommendations. Google needs machine learning to take advantage of their godlike data sets to give users the dopest experience.
There are three different crowds that use machine learning researchers, data scientists, and wizards 😀 “I mean developers”. Ideally they can all use the same tool set to collaborate with each other and improve their efficiency. Tensorflow was a solution they created to help solve this problem.
Google doesn’t just have a lot of data, they also have the world’s largest computers. So the library was built to scale, it was made to run on multiple CPUs or GPUs and even mobile operating systems and it has several wrappers in several languages my favorite one is Python. Cuz I just hate objective-c. 😀
TensorFlow™ is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google’s Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.