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.
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Unlocking Vision: A Beginner's Guide to How Computers 'See'
A beginner's guide to deep computer vision, explaining how Convolutional Neural Networks (CNNs) learn to 'see.'
Teaching an AI to Think: A Beginner's Guide to Reinforcement Learning
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.
Beyond Static Data: An Introduction to Recurrent Neural Networks (RNNs)
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.
Supercharge Your Image Classifier: An Intro to Transfer Learning
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.
Building Your First Image Classifier: A Deep Dive into CNNs
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.
From Pixels to Predictions: Building Your First Fashion Classifier with Keras
A step-by-step walkthrough guide to create your first image classification model.
Chat with Your Documents: How RAG Connects LLMs to Your Private Data
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.