huazai-beyond121 Goto Github PK

an-introduction-to-statistical-learning

This repository contains the exercises and its solution contained in the book An Introduction to Statistical Learning

anatomyofmatplotlib

Anatomy of Matplotlib -- tutorial developed for the SciPy conference

atlas

Datasets, code and virtual workspace for the Climate Change ATLAS

bda_course_aalto

Bayesian Data Analysis course at Aalto by Aki Vehtari

books

Source code for 100+ books, kept here for quick reference

cheatsheets

RStudio Cheat Sheets

climate-change-data

:earth_africa: A curated list of APIs, open data and ML/AI projects on climate change

complex-network

复杂网络研究资源整理和基础知识学习

data

Data for programming

datasciencepython

common data analysis and machine learning tasks using python

epicon.mycobiome

era5analysis

Download and analyse ERA5 data from the Climate Data Store.

gghpcc

A simple tools to draw combination charts. Now it just can draw mantel's test plot.

gridstudio

Grid studio is a web-based spreadsheet application with full integration of the Python programming language.

hmm

Python Hidden Markov Models framework

hovmoller

NumPy / Matplotlib hovmoller diagram

introtodeeplearning

Lab Materials for MIT 6.S191: Introduction to Deep Learning

jupyter

Repository containing Jupyter Notebooks for most of the blog posts on my blog. For example, there are data visualization, data manipulation, and data analysis code examples in the Notebooks

machine-learning-notes

周志华《机器学习》手推笔记

ncomms-codes

ncomms-sourcedatafile

nndl.github.io

《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning

notes

numpy-ml

Machine learning, in numpy

pangeo-cmip6-examples

Examples of analysis of CMIP6 data using xarray and dask

pcr-globwb_model

PCR-GLOBWB (PCRaster Global Water Balance) is a large-scale hydrological model intended for global to regional studies and developed at the Department of Physical Geography, Utrecht University (Netherlands). Contact: Edwin Sutanudjaja ([email protected]).

persistence_in_happi

physics-based-deep-learning

Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond

probabilistic-programming-and-bayesian-methods-for-hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

project-template

CMIP6 Hackathon Project Template