Resources for developers using Python for scientific computing and quantitative analysis
TensorFlow Lite is a framework for running lightweight machine learning models, and it’s perfect for low-power devices like the Raspberry Pi! This video shows how to set up TensorFlow Lite on the Raspberry Pi for running object detection models to locate and identify objects in real-time webcam feeds, videos, or images.
This document serves as an introduction, crash course, and quick API reference for TensorFlow 2.0.
TensorFlow 2 is now live! This tutorial walks you through the process of building a simple CIFAR-10 image classifier using deep learning. In this tutorial, we will:
The code in this tutorial is available here.
Advanced machine learning everyone can use. Stage data. Build models with no code. Manage models in production.
One of the most common utilizations of TensorFlow and Keras is the recognition/classification of images. If you want to learn how to use Keras to classify or recognize images, this article will teach you how.
A tutorial on how to build a GitHub App that predicts and applies issue labels using Tensorflow and public datasets.
