To-Be is a machine learning challenge on CodaLab Platform about Mortality Prediction. The challenge aims to adress the problems of medical imbalanced data classification.
I worked in a team of 3 to solve the challenge and we were able to achieve a score of 77% and rank in the top 3. We used a LGBMClassifier and a mix of two resampling techniques (RandomUnderSampler and BorderlineSMOTE).
Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort
Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application (with docker-compose).
本项目复现李航《统计学习方法》每一章节的算法 特点： 笔记摘要：在每个文件开头都会有一些核心的摘要 pythonic：这里会用尽可能规范的方式来实现，包括编程风格几乎严格按照PEP8 循序渐进：前期的算法会更list的方式来做计算，可读性比较强，后期几乎完全为numpy.array的计算，并且辅助详
Merlion is a Python library for time series intelligence. It provides an end-to-end machine learning framework that includes loading and transforming data, building and training models, post-processi
timeseries-generator This repository consists of a python packages that generates synthetic time series dataset in a generic way (under /timeseries_ge
Self Organising Map for Clustering of Atomistic Samples - V2 Description Self Organising Map (also known as Kohonen Network) implemented in Python for
AutoTS AutoTS is a time series package for Python designed for rapidly deploying high-accuracy forecasts at scale. There are dozens of forecasting mod
learn python in 100 days, a simple step could be follow from beginner to master of every aspect of python programming and project also include side project which you can use as demo project for your
The purpose of this project is create a classification model capable of accurately predicting the price of secondhand cars. The data used for model building is open source and has been added to this
MLND-Capstone My capstone project for Udacity's Machine Learning Nanodegree Lane Detection with Deep Learning In this project, I use a deep learning-b
Simplify stop motion animation with machine learning.
2021 Machine Learning Security Evasion Competition This repository contains code samples for the 2021 Machine Learning Security Evasion Competition. P
Reproducibility and Replicability of Web Measurement Studies This repository holds additional material to the paper "Reproducibility and Replicability
An Open Source Project from the Data to AI Lab, at MIT MLPrimitives Pipelines and primitives for machine learning and data science. Documentation: htt
-ML-Kaggle-Titanic-Problem-using-LogisticRegrission here you will find the solution for the titanic problem on kaggle with comments and step by step c
Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. 📚 docs • 📖 demo notebooks Modern
Diabetes Disease Prediction This is a machine Learning mode which tries to determine if a person has a diabetes or not. Data The dataset is in comma s
Machine Learning Research 1. Project Topic 1.1. Exsiting research Benmark: https://paperswithcode.com/sota ACL anthology for NLP papers: http://www.ac
htsprophet Hierarchical Time Series Forecasting using Prophet Credit to Rob J. Hyndman and research partners as much of the code was developed with th
ai-webshell-detect 机器学习检测webshell,利用textcnn+简单二分类网络,基于keras,花了七天 检测原理: 从文件熵 文件长度 文件语句提取出特征,然后文件熵与长度送入二分类网络,文件语句送入textcnn 项目原理,介绍,怎么做出来的
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