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Recently, I was working on a data visualization project where I needed to create multiple stacked bar charts dynamically using Python. The challenge was that I had dozens of categories, and writing each plt.bar() line manually wasn’t practical. That’s when I realized how powerful a simple for loop in Python could be for automating stacked … Read more >>
Recently, I was working on a Python data visualization project where I needed to display the same dataset on two Y axes in a single Matplotlib chart. At first, I thought this would be a simple task, but I quickly realized that setting up dual Y axes in Matplotlib can be a bit tricky if … Read more >>
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 >>
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 >>
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