Machine Learning Algorithms ( Desion Tree, XG Boost, Random Forest )
Overview
Time Series Prediction with tf.contrib.timeseries
TensorFlow-Time-Series-Examples Additional examples for TensorFlow Time Series(TFTS). Read a Time Series with TFTS From a Numpy Array: See "test_input
Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray
A unified Data Analytics and AI platform for distributed TensorFlow, Keras and PyTorch on Apache Spark/Flink & Ray What is Analytics Zoo? Analytics Zo
Mixing up the Invariant Information clustering architecture, with self supervised concepts from SimCLR and MoCo approaches
Self Supervised clusterer Combined IIC, and Moco architectures, with some SimCLR notions, to get state of the art unsupervised clustering while retain
A Python package for time series classification
pyts: a Python package for time series classification pyts is a Python package for time series classification. It aims to make time series classificat
Dive into Machine Learning
Dive into Machine Learning Hi there! You might find this guide helpful if: You know Python or you're learning it 🐍 You're new to Machine Learning You
Markov bot - A Writing bot based on Markov Chain for Data Structure Lab
基于马尔可夫链的写作机器人 前端 用html/css完成 Demo展示(已给出文本的相应展示) 用户提供相关的语料库后训练的成果 后端 要完成的几个接口 解析文
monolish: MONOlithic Liner equation Solvers for Highly-parallel architecture
monolish is a linear equation solver library that monolithically fuses variable data type, matrix structures, matrix data format, vendor specific data transfer APIs, and vendor specific numerical alg
Transpile trained scikit-learn estimators to C, Java, JavaScript and others.
sklearn-porter Transpile trained scikit-learn estimators to C, Java, JavaScript and others. It's recommended for limited embedded systems and critical
Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Machine Learning
Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Machine Learning
The Fuzzy Labs guide to the universe of open source MLOps
Open Source MLOps This is the Fuzzy Labs guide to the universe of free and open source MLOps tools. Contents What is MLOps, anyway? Data version contr
Auto updating website that tracks closed & open issues/PRs on scikit-learn/scikit-learn.
Repository Status for Scikit-learn Live webpage Auto updating website that tracks closed & open issues/PRs on scikit-learn/scikit-learn. Running local
使用数学和计算机知识投机倒把
偷鸡不成项目集锦 坦率地讲,涉及金融市场的好策略如果公开,必然导致使用的人多,最后策略变差。所以这个仓库只收集我目前失败了的案例。 加密货币组合套利 中国体育彩票预测 我赚不上钱的项目,也许可以帮助更有能力的人去赚钱。
This is my implementation on the K-nearest neighbors algorithm from scratch using Python
K Nearest Neighbors (KNN) algorithm In this Machine Learning world, there are various algorithms designed for classification problems such as Logistic
ML Kaggle Titanic Problem using LogisticRegrission
-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
MLBox is a powerful Automated Machine Learning python library.
MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle
A data preprocessing package for time series data. Design for machine learning and deep learning.
A data preprocessing package for time series data. Design for machine learning and deep learning.
onelearn: Online learning in Python
onelearn: Online learning in Python Documentation | Reproduce experiments | onelearn stands for ONE-shot LEARNning. It is a small python package for o
Python bindings for MPI
MPI for Python Overview Welcome to MPI for Python. This package provides Python bindings for the Message Passing Interface (MPI) standard. It is imple
Python based GBDT implementation
Py-boost: a research tool for exploring GBDTs Modern gradient boosting toolkits are very complex and are written in low-level programming languages. A
Implementation of K-Nearest Neighbors Algorithm Using PySpark
KNN With Spark Implementation of KNN using PySpark. The KNN was used on two separate datasets (https://archive.ics.uci.edu/ml/datasets/iris and https: