Open Data Science (ODSC) Podcast: Alex Castrounis on Data Science

An Open Data Science (ODSC) podcast featuring Alex Castrounis speaking about the field of data science and on being a data scientist.

Cloud Computing and Architecture for Data Scientists

This article covers the fundamentals of cloud computing and architecture for data scientists and data science applications.

Advanced Analytics Packages, Frameworks, and Platforms by Scenario or Task

Which packages, frameworks, and/or platforms to use for a given scenario or task involving artificial intelligence, machine learning, and advanced analytics.

Production vs Development Artificial Intelligence and Machine Learning

Production vs Development Artificial Intelligence and Machine Learning: Offline (batch) vs online vs automated learning, real-time and distributed processing, and more.

Python vs R for Artificial Intelligence, Machine Learning, and Data Science

This article covers Python vs R vs other languages for data science, machine learning, and artificial intelligence (AI), including which to use and why.

Scalable Software and Big Data Architecture - Big Data and Analytics Architectural Patterns

Part 3/3 of the 'Scalable Software and Big Data Architecture' series. This article covers big data and analytics architectural patterns.

Machine Learning: FinTech’s Secret Weapon Against Fraud

In today's digital age, fraud detection and prevention has never been more important. Machine learning is the perfect weapon to battle financial industry fraud.

Goal-Driven Artificial Intelligence and Machine Learning

A description and overview of Alex Castrounis' Goal-Driven Artificial Intelligence and Machine Learning class on Skillshare.

Scalable Software and Big Data Architecture - Software Architectural Patterns and Design Patterns

Part 2/3 of the 'Scalable Software and Big Data Architecture' series. This article covers software architectural patterns and design patterns.

What Is Data Science, and What Does a Data Scientist Do?

This article describes the "pillars" of data science expertise, the role and responsibilities of a data scientist, differences between related roles, and the data scientist's toolbox.