Your First Deep Dive into Neural Networks: A Beginner's Guide.
Understand the core concepts of Deep Neural Networks.Learn its major components and magic behind how it learns.
Understand the core concepts of Deep Neural Networks.Learn its major components and magic behind how it learns.
A beginner's guide to deep computer vision, explaining how Convolutional Neural Networks (CNNs) learn to 'see.'
This guide explains what MCP servers are, how to use them to connect your AI to apps like Obsidian and YouTube, and even how to build your own.
My first blog
A beginner's guide to Reinforcement Learning, focusing on the Q-Learning algorithm. The post details how to build and update a Q-Table, balancing exploration and exploitation to teach an agent through trial and error.
Explanation of what Retrieval-Augmented Generation (RAG) is, positioning it as a cost-effective way to connect large language models to private, up-to-date information.
A hands-on tutorial for building a text-generating AI using a Recurrent Neural Network (RNN). The guide covers everything from encoding the text and creating training sequences to building, training, and finally using the model to generate new, original text in a similar style.
A step-by-step tutorial on using transfer learning to build a highly accurate image classifier. It demonstrates how to load a pre-trained model (MobileNet V2), freeze its layers to preserve its learned knowledge, and then add and train a new custom classifier on top.
A practical tutorial on building a Convolutional Neural Network (CNN) for image classification using the CIFAR-10 dataset. Walk through the entire workflow, from data preparation and model architecture design to training and evaluation.
A step-by-step walkthrough guide to create your first image classification model.