Showing 19 of 19 projects
A 12-week, 26-lesson curriculum teaching classic machine learning using Scikit-learn through hands-on projects and quizzes.
A visualizer for neural network, deep learning, and machine learning models across multiple frameworks.
Python implementations of popular machine learning algorithms from scratch with interactive Jupyter demos and mathematical explanations.
A curated collection of tutorials, articles, and resources for learning machine learning and deep learning topics.
A topic-wise curated list of machine learning and deep learning tutorials, articles, and resources for developers and data scientists.
A low-code declarative framework for building custom LLMs, neural networks, and other AI models with YAML configurations.
A low-code declarative framework for building custom LLMs, neural networks, and other AI models with YAML configurations.
A JavaScript library for client-side NSFW image detection using TensorFlow.js.
A high-performance Python DataFrame library for lazy out-of-core processing and visualization of billion-row datasets at interactive speeds.
An open-source MLOps/LLMOps suite for experiment management, data management, pipelines, orchestration, scheduling, and model serving.
A debugging and visualization tool for data science, deep learning, and reinforcement learning in Jupyter Notebook.
A Python machine learning toolkit for time series analysis with scikit-learn compatible API.
A curated list of research papers, datasets, and resources for anomaly detection in time-series, video, and image data.
A uniform interface to run deep learning models from multiple frameworks like TensorFlow, PyTorch, and Keras in C++ and Python.
Convert PyTorch models to Keras (TensorFlow backend) for deployment and interoperability.
A Ruby library for text classification with Bayesian, LSI, logistic regression, k-NN, and TF-IDF algorithms.
A high-level machine learning library for Go with a Keras-like API, built on Gorgonia.
A Clojure dataset manipulation library providing a dplyr-like API on top of tech.ml.dataset.
A deep similarity learning-based type inference tool for Python that provides ML-powered type auto-completion.
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