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500+ ML/AI interview Q&A with runnable code — covers ML fundamentals, deep learning, NLP, PyTorch, scikit-learn pipelines, and system design.
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Friendly machine learning for the web!
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A set of functions to support the development of machine learning algorithms.
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A Julia machine learning framework.
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A simple Machine Learning Framework written in Swift. Currently features Simple Linear Regression, Polynomial Regression, and Ridge Regression.
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No need to keep checking your training, just one import line and you'll know the second it's done.
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Open-source project that organizes links and resources for browsing websites, collections, or subject directories.
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A library consisting of useful tools for data science and machine learning tasks.
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Open source 3D human modeling toolkit for pose estimation, mesh recovery, and research workflows.
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A modular active learning framework for Python, built on top of scikit-learn.
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Visual testing tool for MCP servers.
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ModelFox is a platform for managing and deploying machine learning models.
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OpenAI compatible API for LLMs and embeddings (LLaMA, Vicuna, ChatGLM and many others).
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Global, black box optimization engine for real world metric optimization by Yelp.
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List of molecular design using Generative AI and Deep Learning.
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Montague is a semantic parsing library for Scala with an easy-to-use DSL.
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CEA-List's CAD framework for designing and simulating Deep Neural Network, and building full DNN-based applications on embedded platforms.
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Llama3 implementation one matrix multiplication at a time.
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A Natural Adversarial Language Processing framework built over Tensorflow.
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General natural language facilities for node.
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Code samples for my book "Neural Networks and Deep Learning" [DEEP LEARNING].
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A PyTorch implementation of DeepDream.
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A parallel neural net microframework.
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A PyTorch implementation of Justin Johnson's neural-style (neural style transfer).