Learning Machine Learning - New Beginnings

Picture of a seedling

New Beginnings - Rendered in H16 and Mantra
© 2017 Sam Swift-Glasman

This site is an effort to document my journey as an artist/developer in the field of 3d Animation, applying my knowledge and experience into my explorations in the fields of Data Science, Complexity Science and Machine Learning.

So far I have spent about a year of research, trying to figure out where to take this site and progress my general interest in Machine Learning into a more solid foundation. I have finally found a source which can provide some structure to my studies - IBM have graciously shared a sylabus for the iniatiate - check out the link below

ibm-the-mathematics-of-machine-learning

As I've shared the link, I won't bother to restate what's there, but in summation, the key areas of study that are outlined are:

  1. Linear Algebra
  2. Probability Theory and Statistics
  3. Multi-variate Calculus
  4. Algorithms and Complex Optimization
  5. Others (Complex Analysis, Topology,Information Theory ect)

 

Luckily for me, these are also all key areas of study in the field of computer graphics so I have had at least some limited experience in all of the above. Hopefully this will help me explore each in detail and relate them into simple demonstrable graphics examples using my platforms of choice Houdini and Python.

The main sources of information that I use on a daily basis to develop my understanding all deserve a special mention here ( as each are amazing)

https://www.khanacademy.org/

https://www.scratchapixel.com/

https://betterexplained.com/

the essence of linear algebra

sentdex

 

happy learning all, i hope you enjoy reading this all as much as I enjoy sharing it!

Sam Swift-Glasman

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  1. Thanx 4 the learning path. 🙂

    MAT 3 months ago Reply