Feb 25 · 7 min read · Training a machine learning model from scratch sounds exciting — until you realize how much data, time, and computing power it actually requires. Large neural networks often need millions of samples a
Join discussionDec 3, 2025 · 8 min read · Brain Tumor Detection is one of the most popular deep learning problems. I had already worked on this task earlier using basic preprocessing and transfer learning. At that time, my pipeline was simple. I used contour detection to crop only the tumor ...
Join discussionNov 1, 2025 · 7 min read · Welcome back, data adventurers! In our last post, we unlocked the superpower of Transfer Learning. We took a pre-trained "expert" model (MobileNetV2), froze its brain, and just trained a new "head" to classify cats vs. dogs. It was fast, easy, and ga...
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Oct 4, 2025 · 8 min read · Welcome back, fellow data adventurers! So far in our "From Zero to Neuron" series, you've built neural networks to classify handwritten digits and predict house prices. You've seen the raw power of these models when trained from scratch. But here’s a...
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May 25, 2025 · 45 min read · Introduction to LLM Fine-Tuning Large Language Models are revolutionizing AI, but their real magic happens with fine-tuning. This isn't just about making models bigger; it's about making them smarter, faster, and perfectly aligned with the specific n...
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Apr 7, 2025 · 4 min read · 🔍 Introduction In this blog, we’ll walk through a full pipeline for applying transfer learning using BERT (Bidirectional Encoder Representations from Transformers) to a text classification task. We'll use the Hugging Face Transformers library along ...
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Mar 18, 2025 · 8 min read · 7 min read | Published at IEEE ICAIQSA 2024 TL;DR 📋 Enhanced ResNet-50 model achieving 98.46% accuracy on breast tumor classification from ultrasound images Outperformed AlexNet, GoogleNet, and VGG by 6-16% Used Bayesian Optimization + Population-B...
Join discussionFeb 2, 2025 · 11 min read · Data augmentation is a key technique in machine learning to enhance dataset size and diversity by applying transformations like rotation and noise addition, improving model generalization and performance. In Keras, ImageDataGenerator facilitates real...
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Nov 20, 2024 · 4 min read · Welcome to our all-encompassing dive into a fascinating scientific paper: "Efficient Transfer Learning For Video-Language Foundation Models." Our goal is to break down the complex concepts from the paper into straightforward explanations. As we do th...
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Nov 5, 2024 · 8 min read · 1. Introduction Transfer Learning is a machine learning technique where a model developed for a particular task is reused as the starting point for a model on a second, related task. Instead of training a model from scratch, we transfer knowledge fro...
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