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airbus-ship-detection-challenge-2018_8th_place_solution

Kaggle Airbus Ship Detection Challenge 2018 8th place code

airflow

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

akshare

AkShare is an elegant and simple financial data interface library for Python, built for human beings! 开源财经数据接口库

autoencoders-for-anomaly-detection

autokeras

Accessible AutoML for deep learning.

autoviz

Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

awesome-automl-and-lightweight-models

A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.

bayesianoptimization

A Python implementation of global optimization with gaussian processes.

caeml

The Computer Aided Engineering Middleware Library (CAEML) is a Python library for building and running simulation workflows. CAEML is developed by Renumics and is currently in early beta state.

causalml

Uplift modeling and causal inference with machine learning algorithms

causalnex

A Python library that helps data scientists to infer causation rather than observing correlation.

chineseocr

yolo3+ocr

course-v3

The 3rd edition of course.fast.ai

data-science--cheat-sheet

Cheat Sheets

deep-learning

Learning deep learning

deep-learning-1

deep_learning_ai

deepcgp

Deep convolutional gaussian processes.

deephpms

Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations

deltaencoder

This is the tensorflow implementation for the paper "Delta-encoder: an effective sample synthesis method for few-shot object recognition" https://arxiv.org/abs/1806.04734

designing-a-robust-feature-selection-pipeline-

Feature selection with Python

differential-evolution

Single header c++ implementation of Differential Evolution algorithm for general purpose optimization.

differential-evolution-1

A multi-processing, highly configurable, C++ Differential Evolution optimization algorithm implementation

dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

eaopt

:four_leaf_clover: Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)

echostatenetwork

econml

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

few-shot

Repository for few-shot learning machine learning projects

gensim

Topic Modelling for Humans

git-for-win

Git for Windows. 国内直接从官网下载比较困难，需要翻墙。这里提供一个国内的下载站，方便网友下载