1073 Open source projects that are alternatives of or similar to Zenml

µTask is an automation engine that models and executes business processes declared in yaml. ✏️📋

An ongoing list of pandas quirks

Collection of useful data science topics along with code and articles

Quick tutorials on quick things that make each devops day better

A JSON Query Language CLI tool

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

Automate Data Exploration and Treatment

Sematext Agent for monitoring MongoDB

A repository for the source code, notebooks, data, files, and other assets used in the data science and machine learning articles on LearnDataSci

Automatic extraction of relevant features from time series:

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Transpile trained scikit-learn estimators to C, Java, JavaScript and others.

Biosignal Processing in Python

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A PyTorch reinforcement learning library for generalizable and reproducible algorithm implementations with an aim to improve accessibility in RL

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DataPrep — The easiest way to prepare data in Python

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Python training for business analysts and traders

yq is a portable command-line YAML processor

The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)

This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.

Efficient variant-call data storage and retrieval library using the TileDB storage library.

Slides, paper notes, class notes, blog posts, and research on ML 📉, statistics 📊, and AI 🤖.

蓝鲸智云标准运维(SOPS)

experiments with python

This is jenkins plugin to run chef-client on remote host

A curated list of fraud detection papers using graph information or graph neural networks

Career Resources for Data Science, Machine Learning, Big Data and Business Analytics Career Repository

📖 The Official Dash Userguide & Documentation

A Python tool that automatically cleans data sets and readies them for analysis.

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

🔩 Like builtins, but boltons. 250+ constructs, recipes, and snippets which extend (and rely on nothing but) the Python standard library. Nothing like Michael Bolton.

阿水的数据竞赛开源分支

The Art of Data Science

Deep Learning Computer Vision Algorithms for Real-World Use

Lazydata: Scalable data dependencies for Python projects

Code for Machine Learning for Algorithmic Trading, 2nd edition.

Out-of-box Data Science / AI platform | AI/数据科学的瑞士军刀

Probabilistic reasoning and statistical analysis in TensorFlow

A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile

Advanced Pandas Vault — Utilities, Functions and Snippets (by @firmai).

Soccer Analytics in R using OPTA data

A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.

A lightweight stream processing library for Go

Interactive network visualization in Python and Dash, powered by Cytoscape.js

Naming is hard. This wrapper script allows you to use set notation with dynamic host groups.

This repository contains the code to generate predictions of critical violations at food establishments in Chicago. It also contains the results of an evaluation of the effectiveness of those predictions.

ELKI Data Mining Toolkit

Data science portfolio

A collection of Bash scripts and Dockerfiles to install data science Tool, Lib and application

A collection of reference machine learning and optimization models for enterprise operations: marketing, pricing, supply chain

This is a collection of all the code that can be found on my YouTube channel Sigma Coding.

Data Annotation, Data Labeling, Annotation Tooling, Training Data for Machine Learning

Easily install and load packages from the tidyverse

Devops定时调用http接口，定时执行SSH命令的WEB定时任务工具。

All of my recommendations for aspiring engineers in a single place, coming from various areas of interest.

.NET Interactive takes the power of .NET and embeds it into your interactive experiences. Share code, explore data, write, and learn across your apps in ways you couldn't before.

Instant access to many datasets in Python.