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basemaptutorial

A Basemap tutorial for ReadTheDocs

bookreviews

canopybypython

python实现Canopy算法

causalmlcourse

A course on causal machine learning.

choicemodels

Python library for discrete choice modeling

coordtransform

提供了百度坐标（BD09）、国测局坐标（火星坐标，GCJ02）、和WGS84坐标系之间的转换

cs189-su18

d3-sankey-diagram

Sankey diagram for d3

d3-scatterplot

documentation

Plotly's Documentation

download

Lantern官方版本下载 蓝灯 翻墙 科学上网 外网 加速器 梯子 路由

floweaver

View flow data as Sankey diagrams

gap_statistic

Dynamically get the suggested clusters in the data for unsupervised learning.

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

hidden-markov-model

First order HMM with Viterbi, Forward-Backward and Baum-Welch implementations

ipysankeywidget

IPython / Jupyter Sankey diagram widget

keras

Deep Learning for humans

kmodes

Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data

knn

机器学习实战

machine-learning-code-writing

Mathematical derivation and pure Python code implementation of machine learning algorithms.

machinelearning

My blogs and code for machine learning. http://cnblogs.com/pinard

marl-papers

Paper list of multi-agent reinforcement learning (MARL)

marl-papers-with-code

Multi-Agent Reinforcement Learning (MARL) papers with code

marl-resources-collection

A Collection of Multi-Agent Reinforcement Learning (MARL) Resources

ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

mlxtend

A library of extension and helper modules for Python's data analysis and machine learning libraries.

multi-agent-reinforcement-learning-papers

Multi-Agent Reinforcement Learning (MARL) papers

nyc-taxi-data

Import public NYC taxi and Uber trip data into PostgreSQL / PostGIS database, analyze with R

pgmpy

Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks.