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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 >>
Recently, I was working on a project where I had to store multiple pieces of data for each customer, their city, orders, and loyalty points, all in one place. The challenge was simple: how do I store multiple values for a single key in a Python dictionary? If you’ve ever tried to assign multiple values … Read more >>
Recently, I was working on a Python project where I had to merge multiple data sources into a single dictionary. The challenge was to extend an existing dictionary with new key-value pairs efficiently without losing any data. If you’ve ever worked with large datasets in Python, you know how important it is to manage dictionaries … Read more >>
While working on a data analytics project for a U.S.-based retail client, I needed to calculate the total daily sales from a list of transactions. Each value represented the sales amount for a day, stored neatly in a Python list. At first, I thought of using the built-in sum() function, but then I realized there … Read more >>
I was working on a data-cleaning project where I needed to filter a large Python dictionary based on specific conditions. The challenge was simple: I had a dictionary with hundreds of key-value pairs, but I only needed a subset that met certain criteria. If you’ve ever worked with Python dictionaries, you know how powerful and … Read more >>
Working on a Python project where I needed to classify human emotions from facial expressions. The goal was simple, build a deep learning model that could recognize emotions like happiness, sadness, anger, and surprise from images. The challenge, however, was figuring out the best way to do this efficiently using Python. After some trial and … Read more >>
When I first started exploring deep learning projects in Python, one of the most fascinating ideas I came across was traffic sign recognition. It felt rewarding to see a model correctly identify road signs, something that’s crucial for modern driver-assistance systems and autonomous vehicles. In this tutorial, I’ll walk you through how I built a … Read more >>
Working on a project where I needed to classify thousands of product images automatically. The challenge? Building a reliable and accurate image classification model using Python and Keras. I’ve been using Keras for over four years now, and it remains one of my favorite deep learning frameworks. It’s simple, powerful, and integrates beautifully with TensorFlow. … Read more >>
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