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d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.

data-mining

Lecture slides and quizzes for Leskovec, Rajaraman, and Ullman's "Mining of Massive Datasets" Stanford course

data-science--cheat-sheet

Cheat Sheets

data-science-notes

数据科学的笔记以及资料搜集

data-structures-algorithms-python

This tutorial playlist covers data structures and algorithms in python. Every tutorial has theory behind data structure or an algorithm, BIG O Complexity analysis and exercises that you can practice on.

davissml

deep-image-steganography

deep-learning-computer-vision

My assignment solutions for Stanford’s CS231n (CNNs for Visual Recognition) and Michigan’s EECS 498-007/598-005 (Deep Learning for Computer Vision), version 2020.

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

deep-learning-with-deeplearning.ai

Program assignments for the Deep Learning Specialization at Coursera by Andrew Ng

deepembeding

图像检索和向量搜索，similarity learning,compare deep metric and deep-hashing applying in image retrieval

deeplearning.ai-notes

基于Andrew Ng DeepLearning.ai课程的学习笔记

deeplearning_ai_books

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

deeprecommender

Deep learning for recommender systems

deepwalk

DeepWalk - Deep Learning for Graphs

dft-book

A book on modeling materials using VASP, ase and vasp

dog-breed-classification

Classification project for recognition of the dog breed based on a dog image and recommendation system for similar breeds

edureka-lms

expertsystems

Movie recommendation expert system

fastbook

The fastai book, published as Jupyter Notebooks

feature-selection-for-machine-learning

Methods with examples for Feature Selection during Pre-processing in Machine Learning.

feature-selector

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

font-awesome

The iconic SVG, font, and CSS toolkit

fraud-detection-handbook

Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook

fucking-algorithm

刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.

gnn-recsys

Graph Neural Networks for Recommender Systems

gnutella-style-peer-to-peer-p2p-file-sharing-system

graph-embeddings-for-recommender-systems

In this project, we will revisit the problem central to recommender systems: predicting a user’s preference for some item they have not yet rated. Like the Spark recommender from the first project, we will use a collaborative filtering model to explore this problem. Recall that in this model, the goal is to find the sentiment of a user about a particular item Unlike the the first project that used the ALS method, however, we will perform this task using a graphbased technique called DeepWalk.

graph-learn

An Industrial Graph Neural Network Framework

graph-machine-learning

Graph Machine Learning, published by Packt