Event details about Reinforcement Learning with Python, Tensorflow and OpenAI 2-days workshop in San Francisco on December 16, 2017 - watch, listen, photos and tickets ...

Machine learning programming is an in-demand skill. Learn how to program an ML application with Python in this tutorial.

If you are adept at Python and remember your high school algebra, you might enjoy [Oliver Holloway’s] tutorial on getting started with Tensorflow in Python.

This tutorial shed some light on why Python is the preferred language for Machine Learning and AI and listed some of the best ML and AI libraries to choose from, including TensorFlow, SciPy, and ...

TensorFlow prerequisites You need a few prerequisites to fully understand the material I’ll cover. First, you should be able to read Python code. If you don’t know how, the book Learning ...

At the same time, TensorFlow started to play better with standard Python infrastructure such as PyPI and pip, and with the NumPy package widely used by the scientific computing community.

If you want to explore machine learning, you can now write applications that train and deploy TensorFlow in your browser using JavaScript. We know what you are thinking. That has to be slow. Surpri… ...

Google clearly wants the machine learning community to help build TensorFlow into a more mature tool that can accelerate certain fields of research and development.

In the realm of machine learning frameworks, there’s no one-size-fits-all solution. PyTorch and TensorFlow offer distinct advantages that cater to different aspects of the machine learning workflow.

Google today unveiled TensorFlow Quantum for training hybrid quantum-classical algorithms by combining TensorFlow with open source quantum library Cirq.