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apache-spark-2x-machine-learning-cookbook

Apache Spark 2x Machine Learning Cookbook, published by Packt

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

bypass-paywalls-chrome-clean

catch2

A modern, C++-native, header-only, test framework for unit-tests, TDD and BDD - using C++11, C++14, C++17 and later (or C++03 on the Catch1.x branch)

cheatsheets-ai

Essential Cheat Sheets for deep learning and machine learning researchers

chinese_from_dongxiexidian

中文预处理语料

code

code exercise: dbscan(ballTree improve) | ctr(ftrl) | text classification(bayes..) | kmeans | general LR |..

ctrmodel

CTR prediction model based on spark(LR, GBDT, DNN)

deeplearning.ai-solutions

Solutions of assignments and translation to Chinese

deeplearning.ai-summary

This repository contains my personal notes and summaries on DeepLearning.ai specialization courses. I've enjoyed every little bit of the course hope you enjoy my notes too.

deeplearningzerotoall

TensorFlow Basic Tutorial Labs

douban-recommender

基于Spark ML实现的豆瓣电影推荐系统

feathercnn

FeatherCNN is a high performance inference engine for convolutional neural networks.

ftrl_proximal_lr

Multithreaded Asynchronous FTRL Proximal Implementation

germany

idea

instructglm

ChatGLM-6B 指令学习|指令数据|Instruct

interpretable-ml-book

Book about interpretable machine learning

introduction-to-data-science-in-python

For the course on Coursera.org

japan

kaggle-2014-criteo

keras-resources

Directory of tutorials and open-source code repositories for working with Keras, the Python deep learning library

leetcode

:pencil2: LeetCode solutions in C++ 11 and Python3

leetcode_py

leetcodetop

汇总各大互联网公司容易考察的高频leetcode题🔥

libffm

A Library for Field-aware Factorization Machines

lintcode

Java Solutions to problems on LintCode/LeetCode

machine-learning-university-of-washington

Assignments for University of Washington Machine Learning Specialization through Coursera

machine_learning

Codes for Machine Learning instructed by Andrew Ng on Coursera, which were written almost 2 years ago, help it helps

machine_learning_regression

My notes on Machine Learning: Regression, the lectures given by University of Washington on Coursera