Popular GitHub Repositories for Dask Dataframes

BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.

DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration

Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.

A full pipeline AutoML tool for tabular data

Amazon SageMaker Local Mode Examples

?? RumbleDB 1.22.0 "Pyrenean oak" ? for Apache Spark | Run queries on your large-scale, messy JSON-like data (JSON, text, CSV, Parquet, ROOT, AVRO, SVM...) | No install required (just a jar to download) | Declarative Machine Learning and more

Build reliable AI and agentic applications with DataFrames

Distributed XGBoost on Ray

Evaluation Tool for Anomaly Detection Algorithms on Time Series

A crossplatform GUI to plot tabulated data from files (e.g. CSV, Excel, OpenFAST, HAWC2, Flex...), or python pandas dataframes

Machine learning operator & controller for Kubernetes

dask-pytorch-ddp is a Python package that makes it easy to train PyTorch models on dask clusters using distributed data parallel.

? Distributed machine learning made simple.

Declarative TabularData creation for Swift - Convert objects to DataFrames with type-safe, SwiftUI-like syntax

A use case of a reproducible machine learning pipeline using Dask, DVC, and MLflow.

? GemInsights: Unleash Gemini AI on your data! ? Analyze dataframes for valuable insights, replacing traditional data analysis. ? A cutting-edge tool revolutionizes the way you analyze dataframes, offering a paradigm shift from conventional data analysis methods.

A scalable, declarative, low-code framework for real-time and batch feature calculation/management (quant finance, anomaly/fraud detection, etc.), predictive ML training/inference and simulation. Built on top of Ray

Solution to kaggle competition OTTO – Multi-Objective Recommender System: https://www.kaggle.com/competitions/otto-recommender-system

Term 1 Project 3 Design a Sign Language Recognition System by Luke Schoen for Udacity Artificial Intelligence Nanodegree (AIND)

A comprehensive collection of data analysis and machine learning projects, showcasing techniques and models for various data challenges. Dive in to explore code examples, analyses, and machine learning workflows.