Recently in a Python webinar, someone asked me how to check if any element in a list is present in another list using Python. This made me research more about this topic, after experimenting and testing various methods I found three effective methods to accomplish this task. In this article, I will explain all important … Read more >>
When I first started working with Python dictionaries more than a decade ago, I often found myself writing long for loops just to build or transform them. Over time, I discovered dictionary comprehension, a powerful and simple way to create dictionaries in just one line of code. It not only saves time but also makes … 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 >>
While working on a project that involved analyzing customer feedback data from different U.S. states, I had to unpack lists in Python multiple times. At first, it seemed simple, just extract values from a list and assign them to variables. But as my data became more complex, I realized how powerful Python’s list unpacking feature … 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’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 >>
Seaborn plays a big role in modern data science by turning raw data into clear, visual insights. If you know how to use it well, you can communicate complex patterns with ease and precision. This article gives you 51 essential Seaborn questions and answers to help you prep for technical interviews and build real confidence … Read more >>
As a Python developer, working extensively with Matplotlib, I’ve come to appreciate the power of fine-tuning plot aesthetics. One of the subtle yet impactful aspects of a plot is how the tick marks on the axes are displayed. Especially when working with complex data visualizations, controlling the tick marks on the right and left sides … Read more >>
As a React developer, I’ve seen firsthand how performance bottlenecks can creep into even the simplest applications. One common culprit? Unnecessary re-renders of functional components. If you’re building React apps for clients in the USA or anywhere else, optimising your components can drastically improve user experience. In this article, I’ll walk you through how to … Read more >>
When I started working with Python’s Matplotlib library, customizing plots was always a key part of making my data visualizations clear and professional. One common task I often encounter is the need to hide or make invisible the y-axis tick labels without removing the ticks themselves. This helps in creating cleaner plots where the numerical … Read more >>