On November 9, 2015, Google open sourced a software library called TensorFlow. TensorFlow is a software library used for Machine learning and Deep learning for numerical computation using data flow graphs. It can run on multiple CPUs and GPUs
Since machine algorithms run on huge data sets, it is extremely beneficial to run these algorithms on CUDA enabled Nvidia GPUs to achieve faster execution, due to thousands of compute cores.
Its always a bit annoying and time consuming process to get a fast and constistent data science environment running. This is a step by step guide, helping you to install a Anaconda Environment with a runable GPU Kernel in a jupyter Notebook. There are other ways of making your GPU usable for Data Science, but this a very good option for beginners and Windows-User.
Why should I use my GPU to compute in data science? Read this article if you dont know yet.

#gpu #tensorflow #windows #anaconda #cuda