Introduction of Survival Analysis and its application in Python — Survival analysis is a branch of statistics focused on analyzing the expected duration of time until one event occurs. It has been largely used in the healthcare sector, with the main use case being to understand the probability of one’s survival in medical trials. This approach can also be applied…

Exploring the implications of AI-generated content from the legal and ethical aspects — The year 2023 is the rise of Artificial Intelligence, specifically Generative AI. The technology itself isn’t new; numerous tech companies have developed and launched desktop/web/mobile apps with some “generative” components — Maybe you recall having fun with the SimSimi chatbot or have been using the Snapseed background remover feature?

Mistakes can happen anywhere, including at work. Here’s how I cope and learn from them. — I believe everybody has made a mistake. They can happen anywhere at any time, oftentimes triggered by just a small act of sloppiness or an honest miss. They often come uninvited and may evoke feelings of guilt, disappointment, or embarrassment. If it happens at work, there can be more pressure…

Principles, Techniques, and Applications to Harness the Power of Prompts in LLMs as a Data Analyst — Large Language Model (LLM) is on the rise, driven by the popularity of ChatGPT by OpenAI which took the internet by storm. As a practitioner in the data field, I look for ways to best utilize this technology in my work, especially for insightful-yet-practical work as a Data Analyst. LLMs…

How data model deployment differs from other analytics projects — So you have created an ML model which seems to have reliable results. Congratulations! I know from experience that oftentimes it’s not easy to get reliable ML models, especially with limited ML exposure as a Data Analyst. …

Ways to calculate Customer Lifetime Value (CLV) and adjust your product priorities. — Customer Lifetime Value (CLV) is one of the most important metrics in marketing analytics. It calculates the monetary value which we gain from the customer over their time on the platform. Exploring this metric can help us in understanding: The perceived value of our products, as this metric reflects the…

Common to-not-do-lists often overlooked in product experimentation causing poor and unreliable results — We all know product experimentation is important, and its benefits have largely been proven by organizations, enabling data-driven decisions on products, features, and processes. Google was testing 40 shades of blue on a link in the search results, and the right blue shade led to 200M in revenue. Booking.com …

It starts with following the curious mind — Research shows that average professionals spend roughly 80,000 hours at work throughout their entire careers. From Monday to Friday, we spend (at least) around a quarter of our time at work. With this huge time spent, no wonder our work impacts our lives to a large extent. …

Exploring the metadata and color-related features of a photo image for further use in Analytics and ML — When working with image data, object recognition and its application have always been on top of mind for Data Analysts and Data Scientists. There has been very little focus on utilizing the metadata from these images. Truth is, we can get quite a lot of insights from the image metadata…