Lists (13)
Stars
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn and PyTorch.
Catalog, compose, and ship ML—Python simplicity, SQL scale.
Time series forecasting with PyTorch
Jupyter notebooks with exercises for the No bullshit guide to linear algebra.
An end-to-end demo of using BigQuery continuous queries to address an unhealthy fish tank IOT sensor event with ServiceNow.
Code for Allen Downey's book Think Complexity, published by O'Reilly Media.
Python For Nonprofits demonstrates how to use Python to retrieve, analyze, visualize, and share nonprofit data.
Lakekeeper is an Apache-Licensed, secure, fast and easy to use Apache Iceberg REST Catalog written in Rust.
A Python library for fast, interactive geospatial vector data visualization in Jupyter.
📝 An awesome Data Science repository to learn and apply for real world problems.
📊 Path to a free self-taught education in Data Science!
Open Source Data Science Resources.
Distributed pushdown cache for DataFusion
An implementation of chunked, compressed, N-dimensional arrays for Python.
Open-source, cloud-native transactional tensor storage engine
Example notebooks for working with SageMaker Studio Lab. Sign up for an account at the link below!
🧠🔗 From idea to production in just few lines: Graph-Based Programmable Neuro-Symbolic LM Framework - a production-first LM framework built with decade old Deep Learning best practices
Python library for building Pangeo Forge recipes.
The simplest, highest-throughput Python interface to S3, GCS & Azure Storage, powered by Rust.
A lightweight data processing framework built on DuckDB and 3FS.
A high-performance distributed file system designed to address the challenges of AI training and inference workloads.
A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Notebooks for the "Deep Learning with JAX" book