963 Open source projects that are alternatives of or similar to Dalex

H2O.ai Machine Learning Interpretability Resources

A curated list of awesome machine learning interpretability resources.

Machine Learning in R

SF Brigade's Data Science Working Group.

A Julia machine learning framework

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

📍 Interactive Studio for Explanatory Model Analysis

An open source book to learn data science, data analysis and machine learning, suitable for all ages!

Model Agnostics breakDown plots

Human-explainable AI.

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

A language and runtime for distributed, incremental data processing in the cloud

An ongoing list of pandas quirks

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

An open source python library for automated feature engineering

A common, beautiful interface to tabular data, no matter the format

A new kind of IDE for Data Science.

A curated list of data science blogs

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

Support content for my blog

Federated Learning Library: https://fedml.ai

Example project implementing best practices for PySpark ETL jobs and applications.

The purpose of this project is to share knowledge on how awesome Streamlit is and can be

The Hitchhiker's Guide to Data Science for Social Good

Feature exploration for supervised learning

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

Python library to easily log experiments and parallelize hyperparameter search for neural networks

Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath

深度学习在推荐系统中的应用及论文小结。

Study guides for MIT's 15.003 Data Science Tools

Automatic extraction of relevant features from time series:

IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018

📘 The interactive computing suite for you! ✨

Calling Python functions from the Ruby language

DataPrep — The easiest way to prepare data in Python

The AI Application Platform We All Need. Human AND Machine Intelligence. Based on experience building AI solutions at Panasonic: robotics predictive maintenance, cold-chain energy optimization, Gigafactory battery mfg, avionics, automotive cybersecurity, and more.

All course materials for the Zero to Mastery Machine Learning and Data Science course.

The easiest way to automate your data

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

A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.

Data Science Course in a Box

The "Python Machine Learning (2nd edition)" book code repository and info resource

📰 Brazilian government gazettes, accessible to everyone.

Temporary home for fastai v2 while it's being developed

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

A proofreader for your data

Create a dashboard with python!

Learn Julia the hard way!

Lazydata: Scalable data dependencies for Python projects

NFStream: a Flexible Network Data Analysis Framework.

A python binding for crfsuite

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

English and European soccer results 1871-2020

A collection of machine learning examples and tutorials.

A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

ELKI Data Mining Toolkit

Reusable JavaScript library for creating sketchy/hand-drawn styled charts in the browser.

Distributed Deep Learning, with a focus on distributed training, using Keras and Apache Spark.