Bijay Kumar 
I was working on a data visualization project where I needed to show the performance of different product categories across several U.S. regions. I wanted to use a stacked bar chart because it’s an excellent way to display the contribution of each category to the total value. While Matplotlib makes it easy to create bar … Read more >>
When I first started using Matplotlib in Python more than a decade ago, one of the challenges I faced was how to visualize two datasets with different scales on the same chart. For example, I often had to compare U.S. sales revenue and customer satisfaction scores, both important metrics but measured in completely different units. … Read more >>
While working on a data visualization project in Python, I needed to invert the secondary Y-axis in a Matplotlib chart. At first, I thought it would be as simple as flipping the main Y-axis, but I quickly realized the secondary axis behaves differently. In this tutorial, I’ll walk you through how to invert the secondary … Read more >>
Working on a deep learning project where I needed to deploy an image classification model on a mobile device. The challenge was clear: I needed something lightweight yet powerful enough to handle complex image data efficiently. After exploring several architectures, I came across MobileViT, a mobile-friendly Transformer-based model that combines the strengths of Convolutional Neural … Read more >>
Radio buttons are essential form elements that allow users to select one option from multiple choices. As a web developer, you’ll often need to programmatically check or uncheck radio buttons using jQuery. This comprehensive tutorial will show you exactly how to set radio button checked states using jQuery, with practical examples and best practices. Basic … Read more >>
Recently, I was working on a computer vision project where I had to classify hundreds of product images like electronics, clothing, and groceries. While convolutional neural networks (CNNs) are the usual choice, I wanted to explore something different, modern MLP (Multi-Layer Perceptron) models that have been making waves in deep learning research. In this Python … Read more >>
When I first started working with deep learning models in Python, I often faced challenges when a single label represented multiple instances, like a bag of medical images or document patches. That’s when I discovered Attention-Based Deep Multiple Instance Learning (MIL) in Keras, and it completely changed how I approached such problems. In this tutorial, … Read more >>
I was working on a Python project where I needed to classify thousands of images quickly and accurately. At first, I tried using a traditional Convolutional Neural Network (CNN), but the accuracy plateaued after a point. That’s when I decided to explore Vision Transformer (ViT), a model that adapts the Transformer architecture (originally used for … Read more >>
Recently, while mentoring a group of data science students, I was asked how to quickly build a Convolutional Neural Network (CNN) in Python Keras to classify handwritten digits using the MNIST dataset. I realized that although the MNIST dataset is one of the most common starting points for deep learning, many beginners still find it … Read more >>
I worked on a Python project where I needed to classify thousands of product images for an e-commerce client based in the USA. The challenge was to achieve high accuracy without spending days training a deep learning model from scratch. After trying several pre-trained models, I found that EfficientNet gave me the best balance between … Read more >>
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