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    Development Frameworks

Large Language Models Applications

LangChain is a programming framework for using large language models (LLMs) in applications. It provides a standard interface for chains, lots of integrations with other tools, and end-to-end chains for common applications. LangChain can flexibly integrate with the ChatGPT AI plugin ecosystem.

Deep Learning

Lightning AI is a platform to train, deploy, and build AI with PyTorch, lightning fast. It provides a platform to build models and build/publish Lightning Apps (ML workflow templates) that ‘glue’ your favorite ML lifecycle tools together. Lightning AI is the first operating system for AI, allowing you to build AI models and Lightning Apps...

Natural Language Processing

NLTK, or Natural Language Toolkit, is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources. NLTK is used for symbolic and statistical natural language processing, artificial intelligence, information retrieval, and machine learning.

High-Performance Numerical Computing

JAX is a Python library designed for high-performance numerical computing, especially machine learning research. It combines Autograd and XLA for high-performance machine learning research. JAX can automatically differentiate native Python and NumPy functions. It can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives.

Deep Learning

Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Caffe is open source, under a BSD license, and originally developed at the University of California, Berkeley.

Numerical Computing

NumPy is a Python library used for numerical computing. It offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy is widely used for data manipulation and analysis, and it is the foundation of many other libraries, such as SciPy, Pandas, and scikit-learn.

Deep Learning

Keras is a high-level, deep learning API developed by Google for implementing neural networks. It is written in Python and is used to make the process of building and training neural networks easier. Keras acts as an interface for the TensorFlow library and is designed for human beings, not machines, with a focus on enabling...

Machine Learning and Deep Learning

PyTorch is an open-source machine learning framework that accelerates the path from research prototyping to production deployment. It’s based on the Torch library and is used for applications such as computer vision and natural language processing. PyTorch is known for its flexibility and speed.

Deep Learning

Apache MXNet is an open-source deep learning software framework used to train and deploy deep neural networks. It is scalable, allowing for fast model training and deployment. MXNet is designed for both efficiency and flexibility, supporting a wide array of devices.

Machine Learning and Artificial Intelligence

TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks and has a comprehensive, flexible ecosystem of tools, libraries, and community resources. TensorFlow is Python-friendly and makes machine learning and developing neural networks faster.