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  2. fast.ai - Wikipedia

    en.wikipedia.org/wiki/Fast.ai

    The free MOOC "Practical Deep Learning for Coders" is available as recorded videos, initially taught by Howard and Thomas at the University of San Francisco. In contrast to other online learning platforms such as Coursera or Udemy, a certificate is not granted to those successfully finishing the course online. Only the students following the in ...

  3. List of programming languages for artificial intelligence

    en.wikipedia.org/wiki/List_of_programming...

    It is mostly used for numerical analysis, computational science, and machine learning. [6] C# can be used to develop high level machine learning models using Microsoft’s .NET suite. ML.NET was developed to aid integration with existing .NET projects, simplifying the process for existing software using the .NET platform.

  4. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    [3] [4] It is one of the most popular deep learning frameworks, alongside others such as PyTorch and PaddlePaddle. [ 5 ] [ 6 ] It is free and open-source software released under the Apache License 2.0 .

  5. Andrew Ng - Wikipedia

    en.wikipedia.org/wiki/Andrew_Ng

    His machine learning course CS229 at Stanford is the most popular course offered on campus with over 1,000 students enrolling some years. [ 24 ] [ 25 ] As of 2020, three of most popular courses on Coursera are Ng's: Machine Learning (#1), AI for Everyone (#5), Neural Networks and Deep Learning (#6).

  6. Comparison of deep learning software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_deep...

    MATLAB + Deep Learning Toolbox (formally Neural Network Toolbox) MathWorks: 1992 Proprietary: No Linux, macOS, Windows: C, C++, Java, MATLAB: MATLAB: No No Train with Parallel Computing Toolbox and generate CUDA code with GPU Coder [23] No Yes [24] Yes [25] [26] Yes [25] Yes [25] Yes With Parallel Computing Toolbox [27] Yes Microsoft Cognitive ...

  7. Deep learning - Wikipedia

    en.wikipedia.org/wiki/Deep_learning

    Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.