Using NGBoost for probabilistic forecasting in time series analysis with nnetsauce and cybooster libraries.

This post demonstrates the use of the cybooster library for regression and classification tasks using NGBoost (Natural Gradient Boosting).

Real-time pricing with a pretrained probabilistic stock return model, using Python FastAPI and R Plumber

In today’s interconnected world, businesses are no longer confined by borders. The global marketplace offers unprecedented opportunities, but it also presents unique challenges, particularly when it comes to cross-border transactions. Whether expanding into international markets, acquiring foreign assets, or engaging in multinational partnerships, navigating these transactions requires careful legal ...

In this post, we will examine how to manipulate the color of the glyphs in a Bokeh data visualization. We are doing this not necessarily for aesthetic reasons but to convey additional information. Below are the initial libraries that we need. We will load additional libraries as required. pydatasets will ...

In today’s digital-first world, your headshot is often the very first impression you make. Whether it’s on LinkedIn, a company website, or even a conference speaker page, that single image tells a story about who you are. But getting a professional headshot isn’t always simple—booking a ...

A beginner-friendly project introducing AWS Lambda & EventBridge notification service Karan Gupta Sep 6, 2025 Introduction From Babylonians using cloud patterns in 650 BC to predict weather to getting a notification on your phone [1], humans have come a long way towards predicting weather patterns. AI models for weather prediction have evolved like Google’s ...

Thinking about moving your mobile service to a more affordable or flexible carrier? Switching from Verizon to T-Mobile in 2025 has become easier than ever. Whether you want to keep your current phone, transfer your number, or explore new plans, the process is straightforward if you follow the right steps. In ...

Revisiting my 2007-2009 Master's Thesis work on SCR Equity approximation using probabilistic machine learning techniques in R and Python.