|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Recommenders||16,382||8 hours ago||158||mit||Python|
|Best Practices on Recommendation Systems|
|Awesome Pytorch List||14,103||4 months ago||4|
|A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.|
|Mit Deep Learning||9,328||a year ago||15||mit||Jupyter Notebook|
|Tutorials, assignments, and competitions for MIT Deep Learning related courses.|
|Computervision Recipes||8,950||8 months ago||65||mit||Jupyter Notebook|
|Best Practices, code samples, and documentation for Computer Vision.|
|Catboost||7,367||6||6 hours ago||60||September 26, 2022||518||apache-2.0||Python|
|A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.|
|Metaflow||6,993||1||19||5 hours ago||91||July 17, 2023||293||apache-2.0||Python|
|:rocket: Build and manage real-life data science projects with ease!|
|Snorkel||5,570||4||8||2 months ago||21||July 29, 2022||18||apache-2.0||Python|
|A system for quickly generating training data with weak supervision|
|Start Machine Learning||3,589||3 months ago||4||mit|
|A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2023 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!|
|Scikit Learn Videos||3,180||2 years ago||Jupyter Notebook|
|Jupyter notebooks from the scikit-learn video series|
|Awesome Computer Science Opportunities||2,993||2 months ago||10||mit|
|An awesome list of events and fellowship opportunities for Computer Science students|
A curated list of Data Science and Engineering frameworks, tools, libraries and related list of tutorials. This mostly covers python related opensource ones ranging from beginner to intermediate levels.
Apache Spark is a fast and general-purpose cluster computing system. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming.
Apache Airflow (or simply Airflow) is a platform to programmatically author, schedule, and monitor workflows.
Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed.
Library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
NumPy is the fundamental package for scientific computing with Python. Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
Alembic is a database migrations tool written by the author of SQLAlchemy. A migrations tool offers the following functionality:
JupyterLab is the next-generation web-based user interface for Project Jupyter.
JupyterLab enables you to work with documents and activities such as Jupyter notebooks, text editors, terminals, and custom components in a flexible, integrated, and extensible manner. You canarrange multiple documents and activities side by side in the work area using tabs and splitters. Documents and activities integrate with each other, enabling new workflows for interactive computing.
Colaboratory is a free Jupyter notebook environment that requires no setup and runs entirely in the cloud.
With Colaboratory you can write and execute code, save and share your analyses, and access powerful computing resources, all for free from your browser.