It is free, open source software library for ML and AI. It can be used for a variety of tasks but has a focus on training and inference of deep neural networks.

TensorFlow enables you to deploy the models on any environment, say servers, browsers, edge devices, cell phones, CPUs, GPUs, FPGAs and microcontrollers.

It is basically a software library for numerical computation making use of data flow graphs. In the graphs, nodes represent mathematical operations. Edges in the graph represent multi-dimensional data arrays, called tensors which communicate between them.

TensorFlow Applications

It is used for voice recognition, image recognition, sentiment analysis, deep neural network, autonomous cars, optical character recognition, video processing and many more.

It is a powerful tool for wide-ranging ML tasks — NLP, time series analysis, generative models, RL, and anomaly detection.

Learn TensorFlow

One has to setup TensorFlow and load a dataset. Then build an ML model. Train and evaluate this model.

There are several pre-trained models at TensorFlow Hub from Google and research models in the Model Garden.

Before you set up TensorFlow, you must have knowledge of programming concepts, linear algebra and calculus.

You can use 3 Blue 1 Brown’s Essence of Linear Algebra or EdX’s Introduction to Linear Algebra.