ML Fundamentals

Built competitor analyzer (benchmarking 5 competitors, share-of-voice calculation, strategy pattern detection), trend detector (momentum… Continue reading on Me

Every one of these compiles. That is what makes them hard to catch. Continue reading on Medium »

AI systems are not simply retrieving information anymore. They are learning which pathways reliably resolve uncertainty. Continue reading on Medium »

A one-character change to the finite difference formula gives you machine-precision derivatives Continue reading on Medium »

Build and Explain an NLP Pipeline: From Raw Text to Machine Learning Continue reading on Medium »

Today, companies use data to understand what is happening in their business and what may happen next. Continue reading on Medium »

arXiv:2605.11118v1 Announce Type: new Abstract: Personalized storefronts in large e-commerce marketplaces are often assembled from many independent components:

arXiv:2605.11151v1 Announce Type: new Abstract: Offline-to-online reinforcement learning (RL) improves sample efficiency by leveraging pre-collected datasets pr

Have you ever seen one of those brain animations where signals jump from one neuron to another? A few neurons light up, the signal keeps… Continue reading on Me

By Sai Pranav Moluguri Continue reading on Medium »

For a long time, I thought becoming better at Python meant learning harder concepts. Continue reading on Stackademic »

Welcome to the fourth article in the THREATRADAR series. We recommend reading Part 1 Design and Implementation of THREATRADAR: Open-Source… Continue reading on

One of the most important concepts in machine learning is the train-test split. While many beginner projects focus heavily on advanced… Continue reading on Medi

When I was working at RBC, I helped rewrite a legacy quantitative finance pipeline from MATLAB into Python/PySpark on Databricks. Continue reading on Medium »

Artificial intelligence is rapidly transforming industries across the world, and healthcare is emerging as one of the areas with the… Continue reading on Medium

From the secret projects of the Manhattan Project to modern XGBoost: Why the future of trading is a “Multiverse” of probabilities, not a… Continue reading on Me

For years, tabular machine learning has been dominated by gradient-boosted trees like XGBoost, LightGBM, and CatBoost. If you worked on… Continue reading on Wri

A complete blog on Ordinal Encoding, Label Encoding, and One-Hot Encoding with real Python code. Continue reading on Medium »

Brain cells do not grow in rigid layers, why should our models? My previous article describes the ‘Dishbrain’ (lab-grown brain cells… Continue reading on Medium

Forecasting models are often judged by how accurate they appear. Continue reading on Medium »

Modern enterprises generate massive amounts of information every single day through customers’ interactions, operations finance, sales… Continue reading on Medi

Every optimization model assumes you know the inputs. In reality, you rarely do. Continue reading on Operations Research Bit »

A Plain-Language Guide to Supervised and Unsupervised Machine Learning Algorithms Continue reading on Activated Thinker »

You’ve probably heard “Python handles memory automatically” — and that’s true. But automatic doesn’t mean invisible, and it definitely… Continue reading on Medi

In 2026, machine learning has transitioned from research-centric experimentation to the core of production systems, powering everything… Continue reading on Med

Build an XGBoost model to predict the next 1–2 weeks of SKU-level order quantity. Continue reading on Medium »

Build an XGBoost model to predict the next 1–2 weeks of SKU-level order quantity. Continue reading on Medium »

Imagine you’re trying to guide a self-driving car along a predefined path. The goal? Stay as close to that path as possible. But what… Continue reading on Mediu

This research introduces Cosmic Pressure Mechanics (CPM), a deterministic physical paradigm that redefines spacetime as an Active… Continue reading on Medium »

I went into this research convinced I already knew the answer. After more than a decade in People Analytics, the last few years at Meta, I had a working theory

How to build sentiment-aware word representations from IMDb reviews using semantic learning, star ratings, and linear SVM classification The post Learning Word

In complex engineering environments, the real value proposition is human ingenuity together with machine precision.

Step‑by‑step guide to train a custom YOLOv8 model, containerize it with Docker, and serve low‑latency predictions via FastAPI

How ML can change for rare events The post Using Transformers to Forecast Incredibly Rare Solar Flares appeared first on Towards Data Science .

In this post, we dive deep into the architecture and techniques we used to improve Miro’s bug routing, achieving six times fewer team reassignments and five tim

A data science case study applying churn prediction, customer lifetime value modelling, and multi-touch attribution to a real-world… Continue reading on Medium

From graph theory to path optimization Continue reading on Medium »

Most revision systems are fundamentally static. Continue reading on Medium »

dbt's 2026 State of Analytics Engineering found that 72% of data teams prioritize AI-assisted coding, but only 24% prioritize AI-assisted pipeline management. T

You might be overcomplicating your deployment by assuming every AI feature requires a GPU. It is a common engineering grind to manage expensive and heavy infras

You have 100 features. Most of them are correlated. Training is slow. Visualization is impossible....

I’ve been running version 8.04 of my Python-based crypto trading bot live for about a month. Instead...

‎It’s been a while since I last posted. ‎ ‎I’ve been busy learning Python consistently behind the scenes — practicing, making mistakes… Continue reading on Medi

And nobody seems to want to ask if that was the right move. Continue reading on Medium »

A step-by-step guide to understanding distributed data, lazy logic, and your first DataFrame. The post PySpark for Beginners: Mastering the Basics appeared firs

Amershi et al. (2019) studied AI development workflows at Microsoft and reported a now-famous number:...

Understanding Mathematical Modeling and Implementation in Python Continue reading on Medium »

Or, a story about Kubernetes probes, slow model loading, and why “healthy at boot” is not the same as “ready to serve.” Continue reading on Medium »