Working with Rust, TypeScript, React.js. Focusing on distributed systems, microservices, AI, CUDA, graphics programming, osdev, and no-code.
Working with Rust, TypeScript, React.js. Focusing on distributed systems, microservices, AI, CUDA, graphics programming, osdev, and no-code.
This tutorial illustrates one way to train a feed forward neural network based on a CSV file using TensorFlow. After training a model we’ll setup a small REST API to serve requests to predict Iris species based on their sepal length, sepal width, petal length and petal width. The REST API and work flow is meant to be as legible as possible to illustrate how to use these features. I’ve avoided adva
TFlearn is a modular and transparent deep learning library built on top of Tensorflow. It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed-up experimentations, while remaining fully transparent and compatible with it. TFLearn features include: Easy-to-use and understand high-level API for implementing deep neural networks, with tutorial and examples. Fast p
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