Search Results for "learn language"
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8 projects for "learn language" with 2 filters applied:
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Ai-Learn
The artificial intelligence learning roadmap compiles 200 cases
Ai-Learn is an open-source artificial intelligence learning roadmap that aggregates educational materials, tutorials, and practical projects designed to help beginners study AI and machine learning systematically. The repository was created to help learners start self-study programs in artificial intelligence without getting overwhelmed by the large number of available resources. -
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Kodezi Chronos
Kodezi Chronos is a debugging-first language model
Kodezi Chronos is a research project focused on developing a specialized language model designed specifically for debugging software and understanding large code repositories. Unlike general-purpose language models that focus primarily on code generation, Chronos is built to diagnose and repair bugs by analyzing complex relationships across files within a codebase. The project introduces architectural techniques such as Adaptive Graph-Guided Retrieval, which allows the system to navigate large repositories and retrieve relevant debugging information from multiple sources. ... -
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AI-Tutorials/Implementations Notebooks
Codes/Notebooks for AI Projects
AI-Tutorials/Implementations Notebooks repository is a comprehensive collection of artificial intelligence tutorials and implementation examples intended for developers, students, and researchers who want to learn by building practical AI projects. The repository contains numerous Jupyter notebooks and code samples that demonstrate modern techniques in machine learning, deep learning, data science, and large language model workflows. It includes implementations for a wide range of AI topics such as computer vision, agent systems, federated learning, distributed systems, adversarial attacks, and generative AI. ... -
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OpenVINO Notebooks
Jupyter notebook tutorials for OpenVINO
...Many notebooks include end-to-end examples that show how to prepare input data, load optimized models, run inference, and visualize results. The project is particularly useful for developers who want to learn how to optimize machine learning inference pipelines for production environments. -
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Adaptive Intelligence
Adaptive Intelligence also known as "Artificial General Intelligence"
Adaptive Intelligence is the implementation of neural science, forensic psychology , behavioral science with machine-learning and artificial intelligence to provide advanced automated software platforms with the ability to adjust and thrive in dynamic environments by combining cognitive flexibility, emotional regulation, resilience, and practical problem-solving skills. -
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Complete Machine Learning Package
A comprehensive machine learning repository containing 30+ notebooks
...Each notebook introduces theoretical ideas and then demonstrates how to implement them using Python libraries commonly used in data science, such as NumPy, pandas, scikit-learn, and TensorFlow. The repository also includes examples related to natural language processing, computer vision, and data visualization, giving learners exposure to several subfields of machine learning. By organizing the content into modular notebooks, the project allows users to explore topics independently and experiment with the code directly. -
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DialoGPT
Large-scale pretraining for dialogue
DialoGPT is an open-source conversational language model developed by Microsoft Research for generating natural dialogue responses using large-scale transformer architectures. The system is built on the GPT-2 architecture and is designed specifically for multi-turn conversation tasks, enabling machines to produce coherent responses during interactive dialogue. The model was trained on a massive dataset of approximately 147 million conversational exchanges extracted from Reddit discussion threads, allowing it to learn patterns of natural human conversation. ... -
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CodeSearchNet
Datasets, tools, and benchmarks for representation learning of code
CodeSearchNet is a large-scale dataset and research benchmark designed to advance the development of systems that retrieve source code using natural language queries. The project was created through collaboration between GitHub and Microsoft Research and aims to support research on semantic code search and program understanding. The dataset contains millions of pairs of source code functions and corresponding documentation comments extracted from open-source repositories. These pairs allow machine learning models to learn relationships between natural language descriptions and programming code. ...
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