Scikit-Learn is a popular python library for machine learning. It offers simple tools for data analysis and modelling, supporting tasks like classification, regression, and clustering. Built on NumPy and SciPy, it is widely used for both academic and industrial applications

XGBoost is an optimized, scalable machine learning library for supervised learning tasks. It is particulary effective for classification and regression problems, leveraging decision tree ensembles. Known for its speed and performance, XGBoost is widely used in data science competitions and production environments

Catboost is an opensource machine learning algorithm based on gradient boosting for classification and regression tasks. It handles categorical features efficiently without the need for extensive preprocessing. Known for its ease of use, speed and high performance, Catboost is ideal for both small and large datasets.

LightGBM is a fast distributed, high-performance gradient boosting framework. It is designed for larger datasets and supports both classification an regression tasks. Known for its efficiency, LightGBM uses histogram based techniques to speed up training and reduce memory usage.

Keras is an open-source deep learning framework written in python. It provides a simple user friendly interface for building and training neural networks. Keras runs on top of TensorFlow, Theano, or Microsoft Cognitive Toolkit (CNTK), and is widely used for fast prototyping and research in AI

TensorFlow is an open-source machine learning framework developed by Google. It offers a comprehensive ecosystem for building, training, and deploying deep learning models across various platforms. TensorFlow supports both research and production environments, with tools for neural networks, data pipelines and large scale machine learning

PyTorch is an open-source deep learning framework developed by Facebook. It provides a flexible and dynamic computational graph for building and training neural networks. PyTorch is popular for research due to its ease of use, strong support for GPU acceleration, and extensive community contributions

LangChain is a framework designed to simplify the developmnent of applications powered by large language models (LLMs). It helps in building pipelines and workflows that integrate LLMs with external data sources, APIs and tools. LangChain is commonly used for creating AI-driven applications like chatbots, document analysis, and automated-decision making systems.

LlamaIndex is a data framework that connects Large Language Models (LLMs) with external data sources. It helps organize, structure, and retrieve data efficiently for LLM-based applications. LLamaIndex is Widely used for building retrieval augmented generation (RAG) systems

Hugging Face is an AI company known for its open-source libraries focused on natural language processing (NLP) and Machine Learning. It offers tools like transformers, datasets, and diffusers for easy access to state of the art models. Hugging Face also provides a platform for model hosting, sharing and deployment

CNTK is an open-source deep learning framework developed by microsoft. It supports training of deep neural networks with high performance and scalability across CPUs and GPUs. Though less commonly used today, it was known for efficiency in speech, image, and text-based tasks.

OpenCV is a popular library for real time computer vision and image processing. It supports wide range of tasks like object detection, facial recognition and image transformation. OpenCV is used in AI, robotics and augmented reality applications.