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A comprehensive resource for understanding the theoretical foundations of machine learning, with detailed proofs, examples, and references.
A curated collection of AI-related books and resources for developers to learn and experiment with AI concepts.
A comprehensive and fair benchmark for time series forecasting methods, including deep learning and statistical techniques.
A collection of machine learning algorithms for edge devices developed by Microsoft Research India.
A deep learning library for head pose estimation using PyTorch, useful for computer vision applications.
An open-source deep reinforcement learning library that combines several state-of-the-art improvements.
A deep learning library for time series classification, useful for AI developers working with sensor and time-based data.
A Python library for 3D object detection from RGB-D data using deep learning.
Automated machine learning for analytics & production use cases powered by popular ML libraries.
A Python library for silent face anti-spoofing using deep learning, useful for mobile apps and computer vision projects.
An offline deep reinforcement learning library for Python developers working on AI-powered applications.
A curated list of awesome AI, ML, and DL resources, including code, tutorials, and study notes.
A comprehensive collection of machine learning interview questions and solutions for algorithm engineers.
A tutorial for deep learning researchers to understand the basics of distribution probability.
A Python framework for quick implementation of recommender systems using TensorFlow.
A Python library for synthetic data curation and structured data extraction for machine learning models.
A standard framework for modeling deep learning models for tabular data in PyTorch.
Hyperparameter optimization library for TensorFlow and Keras, focused on AI/ML model development.
Grad-CAM is a deep learning visualization technique for interpreting and explaining CNN-based models.
A collection of Python code and resources related to natural language processing tasks like topic modeling, text classification, and machine translation.
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