Chapter 1– category –

Recap of Last Time and Today's Topic Hello! In the last session, we learned about generalization performance, which measures how well an AI model can adapt to new data. Generalization is crucial for ensuring that a model performs well in...

Recap of Last Time and Today's Topic Hello! In the last session, we explored overfitting, a significant problem where a model becomes too closely adapted to the training data, resulting in poor performance on new data. Today, we will dis...

Recap of Last Time and Today's Topic Hello! In the last session, we discussed labels (targets), the "correct answers" used in supervised learning that directly impact the accuracy of AI models. Today, we’ll explore the two main categorie...

Recap of Last Time and Today's Topic Hello! In the last session, we learned about features, the key information extracted from data that forms the basis of AI’s predictions and classifications. Today, we’ll explore labels (targets) in su...

Recap of Last Time and Today's Topic Hello! In the last session, we delved into reinforcement learning, where an AI agent learns optimal actions through trial and error by interacting with its environment. Reinforcement learning is appli...

Recap of Last Time and Today's Topic Hello! In the last session, we learned about unsupervised learning, where AI autonomously identifies patterns and structures from unlabeled data. Today, we’ll discuss a very unique learning method in ...

Recap of Last Time and Today's Topic Hello! Last time, we discussed supervised learning, where AI learns from labeled data and achieves high accuracy in prediction and classification tasks. Today, we will explore another learning method ...

Recap of Last Time and Today's Topic Hello! In the last session, we discussed training and testing of AI models. Understanding how models learn and how to evaluate their learning is a crucial step in maximizing AI’s performance. Today, w...

Quick Recap and Today’s Topic Welcome back! Last time, we explored AI models—the core of how AI learns from data to make predictions or decisions. This time, we’re focusing on how to train (teach) these models and then test them to see h...

Recap of Last Time and Today's Topic Hello again! Last time, we learned about the crucial role of data in AI. Data forms the foundation for AI to learn and make accurate predictions or decisions. Today, we will focus on models, which pla...

Recap of Last Time and Today's Topic Hello! In the last session, we discussed algorithms, the basic methods and procedures that solve problems in AI. Algorithms are key to understanding how AI learns and makes decisions. Today, we’ll tak...

Recap of Last Time and Today's Topic Hello! Last time, we explored deep learning, a powerful technology that enables AI to learn complex patterns and make high-level decisions. Today’s topic is algorithms, a fundamental element that unde...

Recap of Last Time and Today's Topic Hello again! In the last session, we explored machine learning, a core technology of AI. Machine learning, which allows computers to learn and make decisions based on data, forms the foundation of mod...

Recap of Last Time and Today's Topic Hello again! In the last session, we covered the basics of AI, its history, and how it has evolved. Hopefully, you've started to gain a deeper understanding of how AI works and the many fields in whic...

Master AI in 365 Days! An Introduction to the Series Welcome to this 365-day AI course! You’ve probably heard the term “AI” (Artificial Intelligence) many times, but if asked, "What exactly is AI?", you might hesitate to answer. This cou...