Open Source AI Tools for Linux

10 Top Open Source AI Tools for Linux (May 2024):
  https://www.geeksforgeeks.org/10-top-open-source-ai-tools-for-linux/

*** TensorFlow: https://www.geeksforgeeks.org/introduction-to-tensorflow/
****PyTorch: https://www.geeksforgeeks.org/linear-regression-using-pytorch/
    Keras: https://www.geeksforgeeks.org/how-to-install-keras-on-linux/
    Scikit-learn: https://www.geeksforgeeks.org/how-to-install-scikit-learn-on-linux/
    Apache MXNet: https://mxnet.apache.org/versions/1.9.1/
    Theano: https://www.geeksforgeeks.org/how-to-install-theano-on-ubuntu/
*   Caffe: https://www.geeksforgeeks.org/how-to-install-caffe-on-ubuntu/
    OpenCV: https://www.geeksforgeeks.org/how-to-install-opencv-for-python-in-linux/
**  H2O.ai: https://www.geeksforgeeks.org/best-h20-ai-alternatives/
    Fastai: https://docs.fast.ai/   -   https://github.com/fastai/fastai

10 Top Open Source Artificial Intelligence Tools for Linux (Oct 2023) no specific order:
    https://www.tecmint.com/open-source-artificial-intelligence-tools-softwares-linux/
     Deep Learning For Java (Deeplearning4j) - https://github.com/deeplearning4j
*    Caffe – Deep Learning Framework - http://caffe.berkeleyvision.org/
**   H20 – Distributed Machine Learning Framework - https://h2o.ai/
      MLlib – Machine Learning Library - https://spark.apache.org/mllib/
      Apache Mahout - https://mahout.apache.org/
      Open Neural Networks Library (OpenNN) - https://www.opennn.net/
***  TensorFlow - https://www.tensorflow.org/
****  PyTorch - https://pytorch.org/
      Apache SystemDS - https://systemds.apache.org/
      NuPIC - https://www.numenta.com/

Ubuntu - A guide to MLOps:  https://ubuntu.com/engage/mlops-guide
The state of AI in 2022—and a half decade in review (Dec 2022):
    https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2022-and-a-half-decade-in-review

What is Red Hat Enterprise Linux AI (RHEL AI)?  A guide to the open source way for doing AI (May 2024):
    https://www.redhat.com/en/blog/what-rhel-ai-guide-open-source-way-doing-ai
    Granite (from IBM Research): https://huggingface.co/ibm/granite-7b-base
"Large Language Models (LLMs) and services based on them (like GPT and chatGPT) are well-known and increasingly adopted by enterprise organizations. These models are most often closed source, or with a custom license. More recently, a number of open models have started to appear (like Mistral, Llama, OpenELM). ...
LLMs today are large and general-purpose. Red Hat envisions a world of purpose-built, cost- and performance-optimized models, surrounded by world class MLOps tooling placing data privacy, sovereignty, and confidentiality at the forefront."

AI on Linux: A Comprehensive Guide to the Best Tools, Platforms, & Frameworks (July 2023):
https://markaicode.com/ai-on-linux-a-comprehensive-guide-to-the-best-tools-platforms-and-frameworks/
"What are the best AI tools for Linux?

•   Visual Studio Code is a free and open-source code editor that supports many programming languages ... It has many features that make it ideal for AI development. Visual Studio Code also has a large collection of extensions that can enhance its functionality and compatibility with various AI platforms and frameworks ...
•   PyCharm is a powerful and popular IDE for Python development, which is one of the most widely used programming languages for AI. ... PyCharm also has built-in support for many AI platforms and frameworks, such as TensorFlow, PyTorch, Keras, and more...
•   NumPy is a fundamental library for scientific computing in Python, which provides high-performance multidimensional arrays and various mathematical functions and operations. NumPy is essential for AI development, as it enables you to manipulate and process large amounts of data efficiently and easily. NumPy also serves as the basis for many other AI libraries, such as SciPy, Pandas, Scikit-learn, and more. ...
•   SciPy is a library that extends the functionality of NumPy, by providing additional modules and functions for scientific and technical computing, such as linear algebra, optimization, statistics, signal processing, and more. SciPy is useful for AI development, as it allows you to perform various complex calculations and analyses on your data. ...
•   Pandas is a library that provides high-level data structures and tools for data analysis and manipulation in Python. Pandas is useful for AI development, as it enables you to work with various types of data, such as tabular, time series, text, and more. ...
•   Scikit-learn is useful for AI development, as it allows you to implement various machine learning tasks, such as classification, regression, clustering, dimensionality reduction, feature extraction, and more. Scikit-learn also has a consistent and user-friendly interface, which makes it easy to use and integrate with other libraries. ...
•   GCC is a free and open-source compiler that supports many programming languages, including C, C++, Fortran, and more. GCC is useful for AI development, as it allows you to compile and optimize your code for various platforms and architectures, such as x86, ARM, and more. ...
•   GDB is a free and open-source debugger that supports many programming languages, including C, C++, Python, and more. GDB is useful for AI development, as it allows you to inspect and modify the state of your program, find and fix errors, and trace the execution of your code. GDB also has support for various AI platforms and frameworks, such as TensorFlow, PyTorch, Keras, and more. ..."

"What are the best AI platforms for Linux?
AI platforms are software applications that provide a comprehensive and integrated environment for developing, deploying, and using AI applications on Linux.

•   TensorFlow is one of the most popular and powerful AI platforms which provides a flexible and scalable framework for building and running various types of AI applications, such as deep learning, computer vision, natural language processing, and more. It has many features that make it ideal for AI development, such as a high-level API (Keras), a low-level API (TensorFlow Core), a distributed and parallel computing support, a large collection of pre-trained models and datasets, and more. ...
•   PyTorch ... provides a dynamic and expressive framework for building and running various types of AI applications, such as deep learning, computer vision, natural language processing, and more. PyTorch has many features that make it ideal for AI development, such as a dynamic computational graph,native support for Python, a distributed and parallel computing support, a large collection of pre-trained models and datasets, and more. ...
•   Keras is a high-level API that provides a simple and intuitive way to build and run various types of AI applications, such as deep learning, computer vision, natural language processing, and more. Keras is compatible with both TensorFlow and PyTorch, which means that you can use either of them as the backend for your Keras models. ...
•   MXNet ... has many features that make it ideal for AI development, such as a hybrid symbolic-imperative programming model, a multiple-language support, a distributed and parallel computing support, a large collection of pre-trained models and datasets, and more. ..."

"What are the best AI frameworks for Linux?
AI frameworks are software applications that provide a specific and specialized environment for developing, deploying, and using AI applications on Linux. ...

  OpenAI is a research organization that aims to create and promote artificial intelligence that can benefit humanity, without causing harm or being misused. OpenAI has developed and released many AI frameworks for Linux, such as:

•         OpenAI Gym is a framework that provides a collection of environments and tasks for testing and benchmarking various AI algorithms, such as reinforcement learning, evolutionary algorithms, and more. It allows you to compare and evaluate the performance of your AI agents, and learn from the best practices and solutions. ...
•         OpenAI Baselines is a framework that provides a collection of high-quality implementations of various AI algorithms, such as reinforcement learning, imitation learning, and more. It allows you to use and modify the state-of-the-art AI methods, and apply them to your own problems and domains. ...
•         OpenAI Spinning Up is a framework that provides a collection of educational resources and tools for learning and practicing various AI algorithms, such as reinforcement learning, deep learning, and more. It allows you to gain a solid foundation and understanding of the AI concepts and techniques, and improve your AI skills and knowledge. ...

    Hugging Face is a company that focuses on creating and providing natural language processing (NLP) solutions and tools for various domains and applications, such as text generation, text summarization, text classification, and more. Hugging Face has developed and released many AI frameworks for Linux, such as:

•         Transformers is a framework that provides a collection of pre-trained models and pipelines for various NLP tasks, such as text generation, text summarization, text classification, and more. It allows you to use and fine-tune the state-of-the-art NLP models, and apply them to your own data and domains. ...
•         Datasets is a framework that provides a collection of datasets and metrics for various NLP tasks, such as text generation, text summarization, text classification, and more. It allows you to access and load the high-quality NLP data, and evaluate the performance of your NLP models. ...
•         Tokenizers is a framework that provides a collection of tokenizers for various NLP models, such as BERT, GPT, XLNet, and more. It allows you to preprocess and tokenize your text data, and optimize the speed and memory efficiency of your NLP models. ...

    Fast.ai is a company and a community that aims to make AI accessible and practical for everyone, by providing courses, books, software, and resources for learning and applying AI. Fast.ai has developed and released many AI frameworks for Linux, such as:

•         Fastai is a framework that provides a high-level API for building and running various types of AI applications, such as deep learning, computer vision, natural language processing, and more. It allows you to use and customize the best practices and solutions for AI, and apply them to your own problems and domains. ...
•         Fastcore is a framework that provides a collection of low-level utilities & tools for Python development, such as functions, classes, decorators, and more. It allows you to write and optimize your Python code, and enhance the functionality and compatibility of your AI applications. ...
•         Nbdev is a framework that provides a tool for developing and documenting your Python code in Jupyter notebooks. It allows you to write and test your code interactively, and generate documentation and web pages automatically. ..."