Posts in category

Programming


TF Dev Summit ‘19 | tf.function and Autograph Here we show how to construct graphs in tf 2.X. The new API, tf.function, makes it very easy to create and run graphs. See the revamped dev site → https://www.tensorflow.org/ 

TF Dev Summit ’19 | Introducing TensorFlow 2.0 and its high-level APIs At TensorFlow Dev Summit 2019, the TensorFlow team introduced the Alpha version of TensorFlow 2.0! With TensorFlow 2.0, we are consolidating our APIs and integrating Keras across the TensorFlow ecosystem. In this talk, we give an overview of what to expect with TensorFlow …

TF Dev Summit ‘19 | AI Experiments: Making AI Accessible through Play Learn about recently open-sourced creative tools and projects built on top of Tensorflow.js, and how they are being used by makers, developers, and communities around the world. Speaker: Irene Alvarado, Google

TF Dev Summit ’19 | TensorFlow.jl: A Julia Front End to the TensorFlow World Julia is a new dynamic scientific programming language that’s as fast as C while maintaining an easy-to-use syntax with powerful metaprogramming. In this talk, we’ll explore how the TensorFlow.jl package lets you seamlessly combine Julia with TensorFlow, TensorBoard, and your existing …

TF Dev Summit ’19 | What’s new in TensorBoard TensorBoard provides the visualization needed for machine learning experimentation. This talk will cover some exciting new functionality on using TensorBoard within Colab, an improved hyperparameter tuning with TensorFlow, and more. Speaker: Gal Oshri, Product Manager

TF Dev Summit ‘19 | TensorFlow Lite TensorFlow Lite is TensorFlow’s solution for running machine learning across resource constrained platforms. In the talk we will go over the current state of TFLite, as well as the roadmap, from the point of view of four core competencies: conversion, optimization, acceleration, and usability. Speakers: Pete Warden, Software …

TF Dev Summit ’19 | TensorFlow Probability: Learning with confidence TensorFlow Probability (TFP) is a Python library built on TensorFlow that makes it easy to combine probabilistic models and deep learning on modern hardware (TPU, GPU). It’s for data scientists, statisticians, and ML researchers/practitioners who want to encode domain knowledge to understand data and make …

TF Dev Summit ’19 | Reinforcement Learning in TensorFlow with TF-Agents Learn how to use TensorFlow and Reinforcement Learning to solve complex tasks. Speakers: Sergio Guadarrama, Senior Software Engineer Eugene Brevdo, Software Engineer

TF Dev Summit ’19 | Swift For TensorFlow: The Next-Generation Machine Learning Framework TensorFlow is about innovation. In this Swift for TensorFlow session, you will learn about language-integrated automatic differentiation, and tooling optimized for your productivity. Speakers: Chris Lattner, Distinguished Engineer Brennan Saeta, Software Engineer

Overview This guide shows how to install TFLearn. TFLearn Deep learning library featuring a higher-level API for TensorFlow.   Prerequisites Python has been installed Installation on Ubuntu Installation on Windows Optional but recommended. Setup a VirtualEnvironment and Pip has been installed. VirtualEnvironment for Ubuntu   Installation 01. Activate your virtual environment, or skip this step …