AI News, Getting Started with TensorFlow
- On Tuesday, March 6, 2018
- By Read More
Getting Started with TensorFlow
Google's TensorFlow engine, after much fanfare, has evolved in to a robust, user-friendly, and customizable, application-grade software library of machine learning (ML) code for numerical computation and neural networks.
By the end of this book, you’ll have gained hands-on experience of using TensorFlow and building classification, image recognition systems, language processing, and information retrieving systems for your application.
Tinker With a Neural Network Right Here in Your Browser.Don’t Worry, You Can’t Break It. We Promise.
Orange and blue are used throughout the visualization in slightly different ways, but in general orange shows negative values while blue shows positive values.
The data points (represented by small circles) are initially colored orange or blue, which correspond to positive one and negative one.
Machine learning is one of the fastest-growing and most exciting fields out there, and deep learning represents its true bleeding edge.
You will learn to solve new classes of problems that were once thought prohibitively challenging, and come to better appreciate the complex nature of human intelligence as you solve these same problems effortlessly using deep learning methods.
Hands-On Machine Learning with Scikit-Learn and TensorFlow
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- On Thursday, March 21, 2019
Hello World - Machine Learning Recipes #1
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Lecture 1 | Introduction to Convolutional Neural Networks for Visual Recognition
Lecture 1 gives an introduction to the field of computer vision, discussing its history and key challenges. We emphasize that computer vision encompasses a wide variety of different tasks,...
Lesson 6: Practical Deep Learning for Coders
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