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Allen's Projects

ml_cheatsheet icon ml_cheatsheet

A 5-pages only Machine Learning cheatsheet focusing on the most popular algorithms under the hood

ml_cia icon ml_cia

公众号机器学习荐货情报局所有代码

ml_notes icon ml_notes

机器学习算法的公式推导以及numpy实现

ml_pipelines icon ml_pipelines

Using Kafka-Python to illustrate a ML production pipeline

mlxtend icon mlxtend

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

mml-book icon mml-book

Code / solutions for Mathematics for Machine Learning (MML Book)

mml-companion icon mml-companion

This is a companion to the ‘Mathematical Foundations’ section of the book, Mathematics for Machine Learning by Marc Deisenroth, Aldo Faisal and Cheng Ong, written in python for Jupyter Notebook.

mmlspark icon mmlspark

Microsoft Machine Learning for Apache Spark

mmtracking icon mmtracking

OpenMMLab Video Perception Toolbox. It supports Single Object Tracking (SOT), Multiple Object Tracking (MOT), Video Object Detection (VID) with a unified framework.

mnist icon mnist

实现对tensorflow模型的读取,然后封装成web服务

mobile-deep-learning icon mobile-deep-learning

This research aims at simply deploying CNN(Convolutional Neural Network) on mobile devices, with low complexity and high speed.

model-compression icon model-compression

model compression based on pytorch (1、quantization: 8/4/2bits(dorefa)、ternary/binary value(twn/bnn/xnor-net);2、 pruning: normal、regular and group convolutional channel pruning;3、 group convolution structure;4、batch-normalization folding for binary value of feature(A))

models-1 icon models-1

The ONNX Model Zoo is a collection of pre-trained, state-of-the-art models in the ONNX format

models-2 icon models-2

Pre-trained and Reproduced Deep Learning Models (『飞桨』官方模型库,包含多种学术前沿和工业场景验证的深度学习模型)

modelzoo icon modelzoo

A framework to help you build model much more easily, implemented with TensorFlow Eager Execution and Keras

modern-cpp-tricks icon modern-cpp-tricks

Modern CPP Tricks often useful in Coding Interviews and Competitive Programming

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