I’ve spent years working with Keras to build efficient deep learning models, and one challenge I often face is training image classifiers with limited labeled data. Semi-supervised learning, combined with contrastive pretraining, offers a powerful solution. In this tutorial, I’ll walk you through how to use SimCLR, a popular contrastive learning framework, to pretrain your … Read more >>
Recently, I was working on a project where I had to train a model to recognise new categories with very little data. The issue is that deep learning models usually need thousands of examples to learn anything useful. So we need a workaround that allows our model to learn fast, just like a human can … Read more >>
I remember debugging a data pipeline for a large logistics company. The system was crashing randomly, throwing type errors that made no sense at first glance. After hours of digging, I realized the issue wasn’t the logic; it was the data types. Some legacy sensors were sending raw binary data (bytes), while newer APIs were … Read more >>
I still remember the first time I deployed a large-scale data processing pipeline for a major logistics company based in Chicago. We were processing millions of shipping addresses, and the entire system crashed because I hadn’t properly accounted for missing data in the “State” field. It turns out that checking for an empty string in … Read more >>
I still remember the late night I spent debugging a payroll system for a client in Chicago because of a single missing value. The system crashed because I treated an empty string from a database field the same way as a Python None object. I have learned that “nothing” comes in many different shapes and … Read more >>
I still remember the panic I felt during a database migration for a large US healthcare provider when a “Zip Code” column caused the entire pipeline to crash. It was a rookie mistake that taught me a valuable lesson about Python’s dynamic typing system: never assume your data is what you think it is. I … Read more >>
I still remember the first time I spent three hours debugging a production script, only to realize a logical flag I thought was a True boolean was actually the string “True”. It’s a classic mistake that even seasoned developers make, especially when dealing with data coming from APIs or user inputs. Python is dynamically typed, … Read more >>
In this tutorial, I will show you how to add two variables in Python. Adding variables is perhaps the most fundamental operation I perform in my daily coding routine. Whether I am calculating financial data or merging user lists, understanding how Python handles addition is critical. I have spent over a decade building software, and … Read more >>
In this tutorial, I will show you how to check if a variable is empty in Python. Handling empty variables is one of the most common tasks I perform in my daily coding routine. If you don’t handle empty data structures correctly, your application will likely crash or produce unexpected errors. Coming from a background … Read more >>
I’ve been developing React applications for over a decade now, and one thing I’ve learned is that performance optimization is key to building smooth and responsive user experiences. React is powerful, but without proper optimization, your app can become sluggish, especially as it grows. In this article, I’ll share the most effective React component optimization … Read more >>
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