If you are like me and try to follow the principles of DRY, KISS, Design Patterns, Occam’s Razor, and other software engineering best practices then this repo is for you!
NOTE: The latest version of repo is available on Obsidian Publish.
Don't reinvent the wheel (DRTW)
Occam’s Razor: The simplest algorithm that fits the data is usually the best — simple is better. Therefore, avoid focusing on SOTA.
Complex theories do not work, simple algorithms do — Vladimir Vapnik
No Free Lunch Theorem: There is no such thing as “best”.
No Free Lunch Theorem: When the performance of all optimization methods is averaged across all conceivable problems, they all perform equally well. Thus, no one optimum optimization algorithm exists.
As an AI/ML engineer, you should be willing to settle for “good enough” rather than trying to finding the “best” model or approach.
Scrum is a popular project management approach but not really a software development methodology [1]. I prefer using an iterative, agile feature-driven development (FDD) methodology where team members are able to work independently without the rigid constraints of Scrum [2].
This repo contains notes from various articles and other resources on a variety of topics in Artificial Intelligence (AI) and Machine Learning (ML).
Whether or not you find this repo useful will depend on your style of learning and taking notes.
This is a work in progress, so there is probably some content missing and the content is changing.
NOTE: The Medium and TowardsDataSciene articles can be viewed in a Private browser tab without a subscription.
Every software engineer and manager needs to read the following:
T. Demarco, Peopleware: Productive Projects and Teams, 2nd ed., Dorset House, 1999.
F. Brooks, The Mythical Man-Month, Anniversary Edition, Addison-Wesley Professional, 1995.
R. L. Glass, Facts and Fallacies of Software Engineering, Addison-Wesley Professional, 1st ed., ISBN: 0321117425, 2002.
The following are helpful to software engineers:
B. W. Kernighan, The Practice of Programming.
J. Bentley, Programming Pearls.
[1] I. Sommerville, Software Engineering 10th ed., Pearson, ISBN: 978-0133943030, 2015.
[2] P. Bourque and R. E. Fairley, Guide to the Software Engineering Body of Knowledge (SWEBOK), v. 3, IEEE, 2014.