@CC-KEH

How Neural Networks Work: Math, Intuition, and Code

5d ago · 18 min read · Introduction In the last post of our Deep Learning Series, we built a Perceptron, a single neuron that draws a straight line to separate two classes. It has one hard limitation: the moment data is not

Understanding the Perceptron: Intuition, Theory, and Code

Mar 23 · 12 min read · Introduction Deep learning drives many technologies we use daily, such as recommendation systems, speech recognition, and computer vision. Before neural networks evolved into their current complexity,

Understanding Mathematical Transforms in Machine Learning

Feb 22, 2025 · 6 min read · Mathematical transformations are essential in feature engineering, a key step in the machine learning process. Before using data in a model, raw datasets often need preprocessing to improve their quality, clarity, and predictive power. Many real-worl...

Building Chatbots with Memory Capabilities: A Comprehensive Tutorial with LangGraph, Gemini AI, and MongoDB

Dec 9, 2024 · 6 min read · Introduction Chatbots are revolutionizing our interactions with technology. In this blog, we’ll guide you through building a chatbot using LangGraph, Gemini AI, and MongoDB. This system will have memory capabilities, allowing it to retain conversatio...

A Step by Step Guide to Linear Discriminant Analysis (LDA) in Machine Learning

Sep 20, 2024 · 6 min read · Introduction Welcome to the ninth blog post in our Machine Learning series! Today, we'll explore Linear Discriminant Analysis (LDA), a powerful algorithm used for reducing dimensions and classification. By the end of this guide, you'll understand how...