Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web
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Updated
May 7, 2024 - HTML
TensorFlow is an open source library that was created by Google. It is used to design, build, and train deep learning models.
Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web
Source codes for the book "Reinforcement Learning: Theory and Python Implementation"
FaceAPI: AI-powered Face Detection & Rotation Tracking, Face Description & Recognition, Age & Gender & Emotion Prediction for Browser and NodeJS using TensorFlow/JS
Deep Learning Camp Jeju
based on "Hands-On Machine Learning with Scikit-Learn & TensorFlow" (O'Reilly, Aurelien Geron)
Tensorflow implementation of the HarvardNLP paper - What You Get Is What You See: A Visual Markup Decompiler (https://arxiv.org/pdf/1609.04938v1.pdf)
A Simple and easy to use way to Visualise Embeddings!
The code for the book Learning TensorFlow.js by Gant Laborde - Published by O'Reilly Media
Code for the paper "Two-Stream Convolutional Networks for Dynamic Texture Synthesis". Presented at CVPR '18.
Pull stock prices from online API and perform predictions using Long Short Term Memory (LSTM) with TensorFlow.js framework
Use any TensorFlow model in a single line of code
TensorFlow wheels (whl) for aarch64 / ARMv8 / ARM64
Python tools for reading, writing, compiling, simulating quantum computer circuits. Includes numpy and tensorflow backends. “Quantum Space, the final frontier. These are the voyages of the starship Qubiter. Its five-year mission: to explore strange new worlds, to seek out new life and new civilizations, to boldly go where no man has gone before.”
English-French Machine Language Translation in Tensorflow
Fake News Detection using Deep Learning models in Tensorflow
An open AI environment using selenium + docker for training automated web agents
Make pytorch and tensorflow two become one.
In this project, I used Python and TensorFlow to classify traffic signs. Dataset used: German Traffic Sign Dataset. This dataset has more than 50,000 images of 43 classes. I was able to reach a +99% validation accuracy, and a 97.3% testing accuracy.
Created by Google Brain Team
Released November 9, 2015