TensorFlow is an open source software library for numerical computation using data flow graphs. The graph nodes represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture enables you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device without rewriting code. TensorFlow also includes TensorBoard, a data visualization toolkit. 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.
This section contains tutorials demonstrating how to do specific tasks in TensorFlow. If you are new to TensorFlow, we recommend reading the documents in the "Get Started" section before reading these tutorials. These tutorials focus on machine learning problems dealing with sequence data. These tutorials demonstrate various data representations that can be used in TensorFlow. Although TensorFlow specializes in machine learning, the core of TensorFlow is a powerful numeric computation system which you can also use to solve other kinds of math problems.
TensorFlow on AWS GPU instance In this tutorial, we show how to setup TensorFlow on AWS GPU instance and run H2O Tensorflow Deep learning demo. Pre-requisites: To get started, request an AWS EC2 instance with GPU support. We used a single g2.2xlarge instance running Ubuntu 14.04.To setup TensorFlow with GPU support, following softwares should be installed: Troubleshooting: 1) ERROR: Getting java.net.UnknownHostException while starting spark-shell Solution: Make sure /etc/hosts has entry for hostname. The minimum required Cuda capability is 3.5" Solution: Specify 3.0 while configuring TF at: Please note that each additional compute capability significantly increases your build time and binary size.
Complete Guide to TensorFlow for Deep Learning with Python by Jose Portilla will help you learn how to use Google's Deep Learning Framework, TensorFlow with Python. This Deep Learning TensorFlow course is for Python developers who want to learn the latest Deep Learning techniques with TensorFlow. You will understand how Neural Networks work. Then you will build your own Neural Network from scratch with Python. This Deep Learning TensorFlow tutorial will teach you to use TensorFlow for Classification and Regression Tasks.