jeremyfix Goto Github PK

12_taxobservatory

ai4oac2023

airsim

Open source simulator based on Unreal Engine for autonomous vehicles from Microsoft AI & Research

ansible-tuto

Ansible tutorial

ar_track_alvar

AR tag tracking library for ROS

arcade-learning-environment

The Arcade Learning Environment (ALE) -- a platform for AI research.

architecture

Supports de cours d'architecture des ordinateurs avec simulation sous logisim

beamer_gen

Preprocessor to generate LaTeX--beamer code from a more compact language

bebop_sphinx

Documentation related to the use of Bebop drones and the Sphinx simulator

blender_samples

botnavsim

Mobile robot simulation (final year project)

cartographie_turtlebot

Autonomous mapping for Turtlebot

cbow

cgraph

A C++ implementation of computational graphs

chessparse

Some experimental codes to extract with opencv a grid table of a chess game moves

chrome-exp

Some simulation experiments in JavaScript

clean-fid

PyTorch - FID calculation with proper image resizing and quantization steps [CVPR 2022]

cmemsapi

A package to help generating reliable data requests about earth observation and marine related information from Copernicus Marine Database.

computational-graph-editor

config

cuda-sample

CUDA official sample codes

datacom

dcejs

Electron app to connect to the Data Center Enseignement clusters of CentraleSupélec - Metz

dcgan-mnist

PyTorch Implementation of DCGAN

deep_examples

Example scripts for deep learning

deepcs

Python utilitary tools used for the deep learning lab works taught at CentraleSupélec (Metz). See the accompanying site for the lectures and lab works at https://github.com/jeremyfix/deeplearning-lectures

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

deeplearning-lectures

Deep learning lecture materials

deeplearning_demos

Deeplearning demos with remote GPU and TCP client/server

deepops

Tools for building GPU clusters