6565 Open source projects that are alternatives of or similar to Knowledge Distillation Keras

Notes for machine learning

A New, Interactive Approach to Learning Python

A tutorial for Automatic Text Summarization using TextRank algorithm.

Udacity Self-Driving Car Engineer Nanodegree projects.

torchtext使用总结，从零开始逐步实现了torchtext文本预处理过程，包括截断补长，词表构建，使用预训练词向量，构建可用于PyTorch的可迭代数据等步骤。并结合Pytorch实现LSTM.

Notebooks for upcoming fastai book (draft / incomplete)

主要是爬虫与数据分析项目总结，外加建模与机器学习，模型的评估。

Python sample codes for robotics algorithms.

🔥🔥NSFW implement in pytorch（色情图&性感图识别，本程序经过了线上大数据集测试，性能优异效果良好）🔥🔥

Assignments for Berkeley CS 285: Deep Reinforcement Learning (Fall 2020)

Placeholder for VTube Studio

Keras Implementation of Neural Style Transfer from the paper "A Neural Algorithm of Artistic Style" (http://arxiv.org/abs/1508.06576) in Keras 2.0+

Open Sourced Curriculum and Lessons for an Introductory AI/ML Course

Various math-related things in Python code

A collection of Jupyter notebooks for learning Python from the ground up.

Code for "The Face of Art: Landmark Detection and Geometric Style in Portraits"

Probability and Statistics Using Python Data Science Masters Course at UCSD (DSE 210)

Stereo convolutional neural network for depth map prediction from stereo images

A curated list of deep learning image classification papers and codes

Jupyter notebook server extension to proxy web services.

This repository contains the Tutorials for the NPTEL MOOC on Machine Learning.

Code for the Make Your Own Neural Network book

This repository contains code for the paper Learning by Association - A versatile semi-supervised training method for neural networks (CVPR 2017) and the follow-up work Associative Domain Adaptation (ICCV 2017).

A Python package for heart rate variability analysis

机器学习&深度学习资料笔记&基本算法实现&资源整理（ML / CV / NLP / DM...）

Following repo is the solution to Stock Market Prediction using Neural Networks and Sentiment Analysis

Modification of fast.ai deep learning course notebooks for usage with Keras 2 and Python 3.

An application that provides personalized career and job search advice to jobseekers.

website

🛠 All-in-one web-based IDE specialized for machine learning and data science.

李航《统计学习方法》中机器学习模型的LaTeX公式笔记

The Raspberry Turk is a robot that can play chess—it's entirely open source, based on Raspberry Pi, and inspired by the 18th century chess playing machine, the Mechanical Turk.

Label line using matplotlib.

Feature selector is a tool for dimensionality reduction of machine learning datasets

Julia Project website

Face Depixelizer based on "PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models" repository.

All For NLP, especially Chinese.

Repository for sharing the knowledge from the learning path of Kaggle Learning. All contributions welcome :).

MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification

iPython notebook and Android app that shows how to build LSTM model in TensorFlow and deploy it on Android

visualization of CNN in PyTorch

Scenarios, tutorials and demos for Autonomous Driving

StarNet

Small projects to clarify big concepts

C/C++/Python based computer vision models using OpenPose, OpenCV, DLIB, Keras and Tensorflow libraries. Object Detection, Tracking, Face Recognition, Gesture, Emotion and Posture Recognition

BetterNetWork4SSD

CCF-BDCI 2018年汽车行业用户观点主题及情感识别挑战赛 第6名解决方案

Multi dimensional LSTM as described in Alex Graves' Paper https://arxiv.org/pdf/0705.2011.pdf

https://www.udemy.com/python-for-finance-and-trading-algorithms/

Python for chemoinformatics

Official implementation of the Averaged Gradient Episodic Memory (A-GEM) in Tensorflow

A Portfolio of my Data Science Projects

量子コンピュータ初学者のための自習教材

这个项目是基于论文YOLO9000: Better, Faster, Stronger的keras（backend：tensorflow）实现

Solutions and comments to assignments for 2019 Stanford's course on convolutional neural networks

Implementation code for the paper "Generating Natural Language Adversarial Examples"

This book serves as an introduction to a whole new way of thinking systematically about geographic data, using geographical analysis and computation to unlock new insights hidden within data.