Tag: courses

Guidelines for Ethical AI

As AI systems become more prevalent in society, we face bigger and tougher societal challenges. Given many of these challenges have not been faced before, practitioners will face scenarios that will require dealing with hard ethical and societal questions.
There has been a large amount of content published which attempts to address these issues through “Principles”, “Ethics Frameworks”, “Checklists” and beyond. However navigating the broad number of resources is not easy.
This repository aims to simplify this by mapping the ecosystem of guidelines, principles, codes of ethics, standards and regulation being put in place around artificial intelligence.
github.com/EthicalML/awesome-artificial-intelligence-guidelines/

🔍 High Level Frameworks & Principles	🔏 Processes & Checklists	🔨 Interactive & Practical Tools
📜 Industry standards initiatives	📚 Online Courses	🤖 Research and Industry Newsletters
⚔ Regulation and Policy

Links to Awesome Artificial Intelligence Guidelines

This overview of ethical guidelines for Artificial Intelligence is by the same author of the repository of Machine Learning production resources shared earlier this year.

Anomaly Detection Resources

Carnegie Mellon PhD student Yue Zhao collects this great Github repository of anomaly detection resources: https://github.com/yzhao062/anomaly-detection-resources

The repository consists of tools for multiple languages (R, Python, Matlab, Java) and resources in the form of:

Books & Academic Papers
Online Courses and Videos
Outlier Datasets
Algorithms and Applications
Open-source and Commercial Libraries/Toolkits
Key Conferences & Journals

Outlier Detection (also known as Anomaly Detection) is an exciting yet challenging field, which aims to identify outlying objects that are deviant from the general data distribution. Outlier detection has been proven critical in many fields, such as credit card fraud analytics, network intrusion detection, and mechanical unit defect detection.
https://github.com/yzhao062/anomaly-detection-resources

Quick Access — Table of Contents

Free Python Tutorials & Courses, by CourseDuck

CourseDuck founder Michael Kuhlman was nice enough to point me to their overview of curated (&free!) Python courses and tutorials.

This overview is curated in the sense that all resources are rated by CourseDuck’s users. These ratings seem quite reliable, at least, I personally enjoyed their top-3 resources sometime the past years:

Note that all these courses, as well as the curated overview, come free of charge! A great resource for starting data scientists or upcoming pythonistas!