herbertwang-me Goto Github PK

auto-sklearn

azure-tdsp-utilities

Utilities and scripts developed as part of Microsoft's Team Data Science Process for productive data science

bookcode

Source code for my books

bootstrap-admin-template

Metis - Free Bootstrap Admin Dashboard Template

bosen

Parallel ML System - Bosen project

bottle_scikit_learn_web_services

creating machine learning web services using scikit_learn

dlog

golang log consider log saved in different server

dragula

:ok_hand: Drag and drop so simple it hurts

gentelella

Free Bootstrap 3 Admin Template

gobuildweb

A naive in-house tool for building a Golang web application and managing frontend assets.

grumpy

Grumpy is a Python to Go source code transcompiler and runtime.

handsontable

Handsontable Community Edition - JavaScript/HTML5 Spreadsheet Component for Web Apps

hangzhouyunqi2017ppt

incubator-mxnet

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

jsoneditor

A web-based tool to view, edit, format, and validate JSON

jupyterlab

JupyterLab computational environment. This is a very early preview, and is not suitable for general usage yet.

jupyterlab-demo

Demonstrations of JupyterLab

lime

Lime: Explaining the predictions of any machine learning classifier

ml-learning

从调包到调参

mlxtend

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

notes-linear-algebra

线性代数笔记

notes-lsju-machine-learning

机器学习笔记

octest

openapi-specification

The OpenAPI Specification Repository

python-mysql-replication

Pure Python Implementation of MySQL replication protocol build on top of PyMYSQL

quepy

A python framework to transform natural language questions to queries in a database query language.

scikit-learn

scikit-learn: machine learning in Python

shark

Development in Shark has been ended.

sklearn-expertsys

Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models

sparkit-learn

PySpark + Scikit-learn = Sparkit-learn