3 projects for "master" with 2 filters applied:

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    Freshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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  • 1
    TorchCode

    TorchCode

    Practice implementing softmax, attention, GPT-2 and more

    TorchCode is an interactive learning and practice platform designed to help developers master PyTorch by implementing core machine learning operations and architectures from scratch. It is structured similarly to competitive programming platforms like LeetCode but focuses specifically on tensor operations and deep learning concepts. The platform provides a collection of curated problems that cover fundamental topics such as activation functions, normalization layers, attention mechanisms, and full transformer architectures. ...
    Downloads: 1 This Week
    Last Update:
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  • 2
    machine-learning-refined

    machine-learning-refined

    Master the fundamentals of machine learning, deep learning

    machine-learning-refined is an educational repository designed to help students and practitioners understand machine learning algorithms through intuitive explanations and interactive examples. The project accompanies a series of textbooks and teaching materials that focus on making machine learning concepts accessible through visual demonstrations and simple code implementations. Instead of presenting algorithms purely through mathematical derivations, the repository emphasizes geometric...
    Downloads: 1 This Week
    Last Update:
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  • 3
    Practical Machine Learning with Python

    Practical Machine Learning with Python

    Master the essential skills needed to recognize and solve problems

    Practical Machine Learning with Python is a comprehensive repository built to accompany a project-centered guide for applying machine learning techniques to real-world problems using Python’s mature data science ecosystem. It centralizes example code, datasets, model pipelines, and explanatory notebooks that teach users how to approach problems from data ingestion and cleaning all the way through feature engineering, model selection, evaluation, tuning, and production-ready deployment...
    Downloads: 0 This Week
    Last Update:
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