Data Analytics

Image by Author | Canva & ChatGPT   #  Introduction   GitHub has become the go-to platform for beginners eager to learn new programming languages, concepts, and skills. With the growing interest in agentic AI, the platform is increasingly showcasing real projects that focus on "agentic workflows," making it an ideal environment to learn and…

Image by author | Canva   An interviewer's job is to find the most suitable candidates for the advertised position. In doing so, they will gladly set up SQL interview questions to see if they can catch you off guard. There are several SQL concepts at which candidates often fail. Hopefully, you’ll be one of…

Image by Author   Data science projects are notorious for their complex dependencies, version conflicts, and "it works on my machine" problems. One day your model runs perfectly on your local setup, and the next day a colleague can't reproduce your results because they have different Python versions, missing libraries, or incompatible system configurations. This…

Image by Author | ChatGPT   Working with data is everywhere now, from small apps to huge systems. But handling data quickly and safely isn’t always easy. That’s where Rust comes in. Rust is a programming language built for speed and safety. It’s great for building tools that need to process large amounts of data…

Image by Author   When I first started learning about how data science and machine learning could be used outside of finance and marketing, healthcare immediately stood out to me. Not just because it’s a massive industry, but because it literally deals with life and death. That’s when I stumbled into something that kept…

Image by Author   #  Introduction   Stress testing is crucial for understanding how your application behaves under heavy load. For machine learning-powered APIs, it is especially important because model inference can be CPU-intensive. By simulating a large number of users, we can identify performance bottlenecks, determine the capacity of our system, and ensure reliability.…

Image by Editor | ChatGPT   #  Introduction   Neo4j is a powerful database that works with connected data. Unlike traditional databases that use tables, Neo4j uses nodes and relationships. This setup makes it easy to explore complex links in data. Neo4j is popular for projects like social networks, recommendation systems, and network analysis. This…

Image by Author | Canva   #  Introduction   There is no doubt that large language models can do amazing things. But apart from their internal knowledge base, they heavily depend on the information (the context) you feed them. Context engineering is all about carefully designing that information so the model can succeed. This idea…

Image by Author | Canva   #  Introduction   Traditional debugging with print() or logging works, but it’s slow and clunky with LLMs. Phoenix provides a timeline view of every step, prompt, and response inspection, error detection with retries, visibility into latency and costs, and a complete visual understanding of your app. Phoenix by Arize…

Image by Author | Canva   #  Introduction   I understand that with the pace at which data science is growing, it’s getting harder for data scientists to keep up with all the new technologies, demands, and trends. If you think that knowing Python and machine learning will get the job done for you in…