Search Results for "tasks"
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Showing 26 open source projects for "tasks"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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WorkBuddyGuide
A practical, open-source guide to mastering WorkBuddy
WorkBuddy Guide is a community-maintained, open-source practical handbook for learning WorkBuddy through real workplace scenarios. Rather than restating product documentation, it follows tasks from initial setup through repeatable team workflows. The guide covers installation, interface basics, Skills, connectors, APIs, automation, knowledge management, content work, meetings, remote work, and other use cases. Advanced sections address building Skills, multi-agent system design, automation reliability, permissions, acceptance criteria, and fallback planning. ... -
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Recommenders
Best practices on recommendation systems
The Recommenders repository provides examples and best practices for building recommendation systems, provided as Jupyter notebooks. The module reco_utils contains functions to simplify common tasks used when developing and evaluating recommender systems. Several utilities are provided in reco_utils to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several state-of-the-art algorithms are included for self-study and customization in your own applications. ... -
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codex-orange-book
A Full-Link Guide to Using Codex from Installation to Real-World Cases
codex-orange-book is an unofficial open-source guide for learning and applying Codex in real software workflows. It is written as a full learning resource rather than a conventional software package. The guide covers installation, configuration, core concepts, standard workflows, practical examples, and extension paths. It explains Codex App, Codex CLI, Codex IDE Extension, Codex Web, cloud workflows, Skills, MCP, Git, GitHub, automation, and memory-related usage. It is aimed at developers,... -
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LangChain Open Deep Research
Fully open source deep research agent
...Environment settings control model choices, search services, MCP servers, and other research behavior. The repository also includes evaluation scripts for Deep Research Bench, enabling reproducible comparisons across difficult multilingual tasks. -
Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
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AI Researcher
An autonomous AI researcher
AI Researcher is an experimental open-source project that demonstrates how multiple AI agents can collaborate to conduct complex research tasks from start to finish with minimal human intervention. It orchestrates agents that can generate research questions, perform literature reviews, execute experiments, analyze results, and synthesize findings into structured outputs like reports or code. Each agent operates with clear roles — such as researcher, analyst, and summarizer — and they communicate through a task-management interface that ensures progress tracking and iterative refinement. ... -
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DevOps Exercises
Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git
DevOps Exercises is a massive, community-maintained collection of questions, tasks, and mini-challenges that cover the breadth of modern DevOps and platform engineering. It spans Linux, networking, Docker, Kubernetes, CI/CD, monitoring, cloud providers, security, and even soft skills and troubleshooting. The idea is to give candidates and teams a realistic practice ground for interviews, certifications, and day-to-day operational work. -
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Python Zero to Hero for DevOps Engineers
Learn Python from DevOps Engineer point of you
...It places a strong emphasis on DevOps-specific use cases: environment variables, command-line arguments, configuration handling, and automating log analysis or user management tasks are all explicitly woven into the exercises. As you progress, you encounter increasingly rich Python features such as lists (with list comprehensions), dictionaries, sets, operators, and control flow, always tied back to practical automation or infrastructure examples. -
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DIG
A library for graph deep learning research
...It includes unified implementations of data interfaces, common algorithms, and evaluation metrics for several advanced tasks. Our goal is to enable researchers to easily implement and benchmark algorithms. -
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HomeworkHelper
Homework Helper: Organize tasks, meet deadlines. Ideal for ADHD
Homework Helper is a comprehensive and user-friendly application designed to assist students in effectively managing their homework and assignments. It provides a convenient and organized platform to keep track of upcoming tasks, due dates, subjects, and associated details. Developed with a focus on simplicity and usability, Homework Helper aims to support students, including those with ADHD or individuals struggling with task management, in staying organized and achieving academic success. To install the app extract the zip file to a folder of your choice and run HomeworkHelper.exe *DISCLAMER* Some of it was made by ChatGPT -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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python-tutorial
Practical Python tutorials, including Python basics
python-tutorial is a practical Python learning repository that collects examples for everyday programming tasks. It covers Python fundamentals, advanced language features, object-oriented programming, multithreading, databases, data science, Flask development, web crawling, and utility scripting. The project is intended for beginners learning Python and for working developers who want reference implementations for common scripts. Its examples are tested in a Python 3 environment and organized into topic-based directories. ... -
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Practice Python
Part of my daily plan for studying Python
practice-python provides a structured set of small, focused exercises aimed at building fluency with Python fundamentals. The tasks emphasize real coding over passive reading, nudging you to write, run, and iterate on solutions. Exercises commonly target strings, lists, dictionaries, control flow, functions, classes, and common algorithms, reinforcing idiomatic Python patterns. Many problems are intentionally minimal in boilerplate so you can concentrate on logic and clarity. -
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IPython
Command shell for interactive computing in multiple languages
...Extensible tab completion, with support by default for completion of python variables and keywords, filenames and function keywords. Extensible system of ‘magic’ commands for controlling the environment and performing many tasks related to IPython or the operating system. A rich configuration system with easy switching between different setups (simpler than changing $PYTHONSTARTUP environment variables every time). Session logging and reloading. Extensible syntax processing for special purpose situations. Access to the system shell with user-extensible alias system. ... -
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Spinning Up in Deep RL
Educational resource to help anyone learn deep reinforcement learning
...This is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL). For the unfamiliar, reinforcement learning (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning. At OpenAI, we believe that deep learning generally, and deep reinforcement learning specifically, will play central roles in the development of powerful AI technology. To ensure that AI is safe, we have to come up with safety strategies and algorithms that are compatible with this paradigm. ... -
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Scikit-learn Tutorial
An introductory tutorial for scikit-learn
Scikit-learn Tutorial contains the materials for Jake VanderPlas’s introductory scikit-learn tutorial, originally used at major Python conferences. It provides a collection of notebooks that walk attendees from basic machine-learning concepts into practical modeling using the scikit-learn library. The tutorial covers data preparation, model fitting, evaluation, and common algorithms such as classification, regression, clustering, and dimensionality reduction. It is designed for people who... -
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Neural MMO
Code for the paper "Neural MMO: A Massively Multiagent Game..."
Neural MMO is a massively multi-agent simulation environment developed by OpenAI for reinforcement learning research. It provides a persistent, procedurally generated world where thousands of agents can interact, compete, and cooperate in real time. The environment is inspired by Massively Multiplayer Online Role-Playing Games (MMORPGs), featuring resource gathering, combat mechanics, exploration, and survival challenges. Agents learn behaviors in a shared ecosystem that supports long-term... -
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Canorus
Music score editor
Canorus is a free cross-platform music score editor. It supports an unlimited number and length of staffs, polyphony, a MIDI playback of notes, chord markings, lyrics, import/export filters to formats like MIDI, MusicXML, ABC Music, MusiXTeX and LilyPond -
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Evolution Strategies Starter
Code for the paper "Evolution Strategies.."
evolution-strategies-starter is an archived OpenAI research project that provides a distributed implementation of the algorithm described in the paper “Evolution Strategies as a Scalable Alternative to Reinforcement Learning” by Tim Salimans, Jonathan Ho, Xi Chen, and Ilya Sutskever. The repository demonstrates how to scale Evolution Strategies (ES) for reinforcement learning tasks using a master-worker architecture, where the master node broadcasts parameters to multiple workers, and the workers return performance results after evaluation. This approach allows for efficient parallelization and robustness against worker termination, making it ideal for distributed execution on Amazon EC2 spot instances. The codebase supports building custom AMIs with Packer, integrates with MuJoCo for simulation-based experiments, and includes scripts for launching and managing large-scale runs. ... -
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Tasks
Program to manage tasks
Tasks aims management of tasks easy. It allows for more advanced features such as tagging tasks with custom categories, importance, subtasks and dates while also making it easy to create them. All a tasks need to be present is a title! -
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Learning to Learn in TensorFlow
Learning to Learn in TensorFlow
...The design supports both single-variable and high-dimensional problems, and includes tools for evaluating how well a learned optimizer performs on unseen tasks. -
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AlgoTaurus
An educational game to teach programming.
...On Linux -Download the source files -Extract archive -Open terminal in the directory you have copied the files to and type 'python algotaurus.py' Use and discuss AlgoTaurus: Some tasks to solve and discuss: Write a program to find the exit. What does the program do? Try to describe/explain it in a higher level language. How can you be sure that the program works correctly every time? Try to make the program as short as possible. Try to make the program to move as little as possible. Try to minimize the number of lines needs to be executed. ... -
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Matplotlib tutorial
Matplotlib tutorial for beginner
The Matplotlib tutorial repository is designed as a hands-on learning resource to help users — especially Python beginners — get started with Matplotlib for creating plots and charts. It provides a sequence of example scripts and notebooks that cover fundamental plotting tasks: line graphs, histograms, scatter plots, bar charts, customizing axes, labels, legends, and styling. This makes it ideal for someone learning data analysis or exploratory data visualization for the first time and needing concrete, runnable examples rather than abstract explanations. As the tutorial builds progressively, learners can gradually advance from simple static plots to more complex visualizations, learning how to control figure size, add multiple subplots, adjust plot aesthetics, and handle different data types. ... -
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AutoTeach
AutoTeach makes kids study and learn in exchange for internet access.
AutoTeach is a tool that enables parents to supplement The AutoTeach Parent Tool enables parents to supplement their childrens' education without supervision or drama. With AutoTeach you can queue-up activities and tasks that will be dutifully performed at regular intervals. Why will they cooperate like this? Because AutoTeach meters their internet access by using credits which they earn by performing the agenda which you have queued-up for them. The system has potential for many subjects. Everyone, worldwide, is invited to participate. Everything is open-licensed, either Creative Commons or GPL. -
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The sandbox libraries (libsandbox & pysandbox) are an open-source suite of software components for C/C++ and Python developers to create automated profiling tools and watchdog programs. The API's are designed for executing and instrumenting simple (single process) tasks, featuring policy-based behavioral auditing, resource quota, and statistics collecting. The sandbox libraries were originally designed and utilized as the core security module of a full-fledged online judge system for ACM/ICPC training. They have since then evolved into a general-purpose tool for binary program testing, profiling, and security restriction. ...
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denadra
Vocabulary trainer application
You can easily improve your vocabulary with denadra. Create lessons by yourself. -
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A learning-by-testing program to learn quickly, mostly memorizing tasks like vocabulary. Quizdrill supports multiple choice, simple quiz as well as flashcard testing.
