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I was working on a Python data visualization project where I needed to plot a 3D scatter chart using Matplotlib. Everything looked great, except for one thing. The axis ticks were cluttered and not very readable. If you’ve ever faced the same issue, you’re not alone. While Matplotlib provides powerful 3D plotting tools, customizing the … Read more >>
While working on a data visualization project for a U.S.-based analytics firm, I needed to display a large 3D dataset in a way that didn’t look cluttered. The challenge was that overlapping points made it hard to see depth and density. That’s when I decided to make the 3D scatter plot transparent using Python Matplotlib. … Read more >>
When I first started working with Python Matplotlib, I was fascinated by how easily it could visualize complex datasets in 2D. But when I discovered the power of 3D plots, it opened a whole new world of possibilities. In this tutorial, I’ll show you how to create a 3D scatter plot with a line and … Read more >>
Working on a Python data visualization project that required analyzing 3D data points from a manufacturing dataset. I wanted to rotate the 3D scatter plot to examine the relationships between variables from different angles. If you’ve ever tried to visualize 3D data using Matplotlib, you’ve probably noticed that rotation helps you uncover hidden patterns that … Read more >>
Recently, I was working on a project where I needed to classify thousands of product images into multiple categories. Being a Python Keras developer for over four years, I’ve tried several deep learning models, from CNNs to Transformers. In this tutorial, I’ll show you how to perform image classification using the Perceiver model in Keras. … Read more >>
I was working on a deep learning project where I needed a model that could capture spatial relationships more efficiently than traditional convolutional neural networks (CNNs). After exploring various architectures, I came across Involutional Neural Networks, a fascinating concept that reverses the idea of convolution. In this article, I’ll show you how to build an … Read more >>
Working on a computer vision project where I needed to classify hundreds of product images into different categories. As a developer, I always look for efficient deep learning architectures that can deliver strong accuracy without excessive computation. That’s when I came across EANet (External Attention Network), a lightweight yet powerful transformer-based model. In this tutorial, … Read more >>
Working on an image classification project for a U.S.-based retail analytics company, I explored several deep learning architectures. I wanted something lightweight yet powerful enough to classify product images accurately. That’s when I came across ConvMixer, a fascinating model that combines the simplicity of CNNs with the design philosophy of Vision Transformers. In this tutorial, … Read more >>
I was working on a deep learning project where I needed a model that could combine the power of convolutional neural networks (CNNs) and transformers, but without consuming too much memory. That’s when I came across Compact Convolutional Transformers (CCT). These models are designed to be lightweight yet powerful, perfect for mobile and edge devices. … Read more >>
Recently, I worked on a deep learning project to classify chest X-ray images for pneumonia detection using Python and Keras. The challenge was to make the training process faster and more efficient, especially when dealing with thousands of medical images. That’s when I decided to use TPUs (Tensor Processing Units), powerful hardware accelerators that can … Read more >>
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