Machine Learning
================

.. contents:: Table of Contents

Use Cases
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Machine learning (ML) is a subset of artificial intelligence (AI). It is great for making predictions based on historical data. [1]

Use-cases:

-  Image recognition

   -  Identifying objects in an image.

-  Natural language processing (NLP)

   -  Understanding written or vocal speech.

-  Recommendation engines

   -  Predicting what similar products a user might like.

Mathematics
-----------

Machine learning does not always require having a deep knowledge of math. When it is needed, these are the most relevant mathematical subjects a machine learning expert should be familiar with [2][3]:

-  Linear algebra
-  Statistics
-  Differential calculus
-  Integral calculus

Programming Languages
---------------------

More than half of all machine learning programs are built using Python. [4] Here are the top 3 programming languages used [4][5]:

1.  Python
2.  R
3.  Java

Graphics Card Vendors
---------------------

NVIDIA provides the best support for machine learning with its proprietary CUDA library. It is possible to use AMD and Intel graphics cards by using the open source OpenCL library [7] but NVIDIA provides the best performance and compatibility. [6]

Resources
---------

Mathematics [2][3]:

- Books:

   -  `Deep Learning <https://www.deeplearningbook.org/>`__
   -  `Hands-On Mathematics for Deep Learning <https://www.packtpub.com/product/hands-on-mathematics-for-deep-learning/9781838647292>`__
   -  `Mathematics for Machine Learning <https://mml-book.github.io/>`__

-  Videos:

   -  `Khan Academy Math <https://www.khanacademy.org/math>`__

History
-------

-  `Latest <https://github.com/LukeShortCloud/rootpages/commits/main/src/programming/machine_learning.rst>`__

Bibliography
------------

1. "Classification, regression, and prediction - what's the difference?" Towards Data Science. December 11, 2020. Accessed November 7, 2022. https://towardsdatascience.com/classification-regression-and-prediction-whats-the-difference-5423d9efe4ec
2. "A beginner’s guide to the math that powers machine learning." TNW The heart of tech. October 2, 2022. Accessed November 7, 2022. https://thenextweb.com/news/a-beginners-guide-to-the-math-that-powers-machine-learning-syndication
3. "Math for Machine Learning: 14 Must-Read Books." Machine Learning Techniques. June 13, 2022. Accessed November 7, 2022. https://mltechniques.com/2022/06/13/math-for-machine-learning-12-must-read-books/
4. "What is the best programming language for Machine Learning?" Towards Data Science. May 5, 2017. Accessed November 7, 2022. https://towardsdatascience.com/what-is-the-best-programming-language-for-machine-learning-a745c156d6b7
5. "7 Top Machine Learning Programming Languages." Codeacademy. October 20, 2021. Accessed November 7, 2022. https://www.codecademy.com/resources/blog/machine-learning-programming-languages/
6. "How to Pick the Best Graphics Card for Machine Learning." Towards Data Science. September 19, 2022. Accessed November 7, 2022. https://towardsdatascience.com/how-to-pick-the-best-graphics-card-for-machine-learning-32ce9679e23b
7. "Does TensorFlow Support OpenCL?" IndianTechWarrior. Accessed November 7, 2022. https://indiantechwarrior.com/does-tensorflow-support-opencl/