A comprehensive look at AI safety concerns, from current challenges to future risks, with practical approaches to building safer AI systems.
Learn how Mixture of Experts (MoE) works like a team of specialists, each handling what they do best, to solve complex problems.
Discover how Chain of Thought prompting helps AI break down complex problems into simple steps, just like humans do.
Dive into the world of neural networks and deep learning, from basic concepts to practical implementation, with clear examples and intuitive explanations.
Learn why accuracy alone isn't enough and discover the key metrics for properly evaluating machine learning models.
Discover how to transform raw data into meaningful features that improve your model's performance, with practical examples and best practices.
Learn how to properly validate your machine learning models and avoid the pitfalls of overfitting.
Learn how unsupervised learning algorithms discover hidden patterns and group similar items together, with real-world examples and applications.
Explore how machines learn through trial and error, just like humans do, with practical examples from gaming to robotics.
Understand how regression works in machine learning through practical examples, from predicting house prices to estimating sales.
Discover how classification in machine learning works through simple examples, from email spam detection to image recognition.
A beginner-friendly introduction to machine learning concepts, explained with real-world examples and minimal technical jargon.
Learn about data cleaning, deduplication, and how to split your data properly to build effective machine learning models.