fmthoker Goto Github PK

3drotnet

Code for Self-supervised Spatiotemporal Feature Learning by Video Geometric Transformations

awesome

:sunglasses: Curated list of awesome lists

awesome-action-recognition

A curated list of action recognition and related area resources

awesome-deep-vision

A curated list of deep learning resources for computer vision

awesome-knowledge-distillation

Awesome Knowledge Distillation

awesome-knowledge-distillation-1

Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2021)。

awesome-self-supervised-learning

A curated list of awesome self-supervised methods

awesome-skeleton-based-action-recognition

Skeleton-based Action Recognition

coursera_stanford_ml_solutions

cs231n

my assignment solutions for CS231n Convolutional Neural Networks for Visual Recognition

cs231n.github.io

Public facing notes page

decision-tree-in-python-for-continuous-attributes

This code constructs a Decision Tree for a dataset with continuous Attributes. Each training instance has 16 numeric attributes (features) and a classification label, all separated by commas. In deciding which attribute to test at any point, the information gain metric is used. The node test threshold for each potential attribute is set using this same metric i.e. at each point, all the values that exist for a particular attribute in the remaining instances are ordered, and threshold values that are (half way) between successive attribute values are used to find the Information Gain. The threshold value that gives the highest information gain is used. The same attribute can be tested again later in the tree (with a different threshold).

decision_trees

deep-learning-drizzle

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

deep-learning-papers-reading-roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

deeplearning_networks_cnns

eis_test

faceswap

Non official project based on original /r/Deepfakes thread. Many thanks to him!

fast_slam_python

fmthoker.github.io

generative_adversarial_networks_live

knn

learning-guides

:book: PDF slides from various platforms to learn fast :D

machine-learning-notes

My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (1000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(1000+页)和视频链接

milq

Useful code of Manuel Ignacio López Quintero

msom

Implementation of Self organizing Maps (MSOM)

neural-networks

Artificial Neural Networks / Python

neural_net_tensor_flow

neuralnetwork

Simple Back Propagation Neural Network

prml

PRML algorithms implemented in Python