本项目复现李航《统计学习方法》每一章节的算法
特点：
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neurodsp is a collection of approaches for applying digital signal processing to neural time series, including algorithms that have been proposed for the analysis of neural time series. It also inclu
PyFlux PyFlux is an open source time series library for Python. The library has a good array of modern time series models, as well as a flexible array
LiuAlgoTrader is a scalable, multi-process ML-ready framework for effective algorithmic trading. The framework simplify development, testing, deployment, analysis and training algo trading strategies
cuML - GPU Machine Learning Algorithms cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions t
Mixed precision training [0] is a technique that mixes the use of full and half precision floating point numbers during training to reduce the memory bandwidth requirements and improve the computatio
The Greykite library provides flexible, intuitive and fast forecasts through its flagship algorithm, Silverkite.
What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin
Currently a Beta-Version lucidmode is an open-source, low-code and lightweight Python framework for transparent and interpretable machine learning mod
MosaicML Composer MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training. We aim to ease th
Model Serving Made Easy BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models. Supports multi
ETNA Time Series Library Predict your time series the easiest way Homepage | Documentation | Tutorials | Contribution Guide | Release Notes ETNA is an
Welcome MICOM is a Python package for metabolic modeling of microbial communities currently developed in the Gibbons Lab at the Institute for Systems
Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets Datasets Used: Iris dataset,
This project is made to help you scale from a basic Machine Learning project for research purposes to a production grade Machine Learning web service
ARM This jupyter notebook project was completed by me and my friend using the dataset from Kaggle. The world Happiness 2017, which ranks 155 countries
Elephas: Distributed Deep Learning with Keras & Spark Elephas is an extension of Keras, which allows you to run distributed deep learning models at sc
Deepdream Eyes Made in collaboration with Chris George for Art + ML Spring 2019.
Learn Machine Learning Algorithms by doing projects in Python and R Programming Language. This repo covers all aspect of Machine Learning Algorithms.
PySpark (Spark com Python) PySpark é uma biblioteca Spark escrita em Python, e seu objetivo é permitir a análise interativa dos dados em um ambiente d
auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here
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