Have you ever wondered what actually happens between “we have some data” and “there’s an app using AI”? That gap is the machine learning workflow. It is the real journey every ML project takes, and it is far simpler than it sounds. In our last episode, we explored the three ways machines learn: supervised, unsupervised, […]
The Machine Learning Workflow: From Raw Data to a Deployed Model Read More »
A few weeks ago I announced that my Malayalam Whisper model beat the previous best open Malayalam ASR model by 24 WER points. That number is still true. But while getting ready to train a v2 of the model, I decided to actually check something I’d never checked before: was my train/test split clean? It
I Checked My Own ASR Dataset for Leakage — Here’s What I Found Read More »
What Is Machine Learning? Understanding the Types of Machine Learning (Supervised, Unsupervised & Reinforcement) Machine Learning sounds intimidating at first. People imagine complex math, endless equations, and years of study before you can understand anything. That reputation, however, is misleading. Once you break Machine Learning into its core ideas, it becomes surprisingly simple. Machine Learning
Types of machine learning Read More »
Python OOP Basics: Classes, Objects, and the Four Pillars Explained Every large Python project relies on one core idea. That idea is Object-Oriented Programming, or OOP. Once you understand Python OOP basics, you start to see code differently. You stop writing scattered instructions. Instead, you build reusable, organized blueprints for real-world things. This article is
Python OOP Basics: Classes, Objects, and the Four Pillars Explained Read More »
Python programs create data constantly. But that data disappears the moment your program ends — unless you save it. That’s where file I/O steps in. Modules solve a different problem: they let you reuse code instead of rewriting it. This article covers both skills for EP09 of the Intelevo series. Follow along, then practice each
Python File I/O and Modules: Intelevo EP09 Read More »
Python offers many ways to store data. However, two structures stand out for their speed and flexibility: dictionaries and sets. In this article, we explore both concepts clearly. Consequently, you can follow along with EP08 of the Intelevo series and reinforce what you learn on screen. What Is a Dictionary? A dictionary stores data as
Python Dictionaries and Sets: Intelevo EP08 Read More »
What Are Lists and Tuples? Python gives you two powerful ways to store ordered data — lists and tuples. Both hold multiple items in sequence, support indexing, and work with mixed data types. Yet they serve very different purposes, and picking the right one matters more than most beginners realise. Lists are flexible and mutable
Python Lists and Tuples Explained — Intelevo EP07 Read More »
INTELEVO EP 06 – Complete Tutorial for AI & Data Science Introduction You’ve already learned variables, conditions, and loops. But here’s the problem — the moment you need the same logic twice, you copy and paste. That’s fragile code. One small change means you hunt down every copy and fix each one manually. Functions fix
Python Functions: Write Once, Use Everywhere Read More »
INTELEVO EP 05 – Complete Tutorial for AI & Data Science Introduction Imagine you’re a teacher who needs to print grade reports for 150 students. Without loops, you’d write 150 individual print statements. With loops? Just five lines of code. That’s the power of iteration. Loops are one of the most powerful features in programming.
Loops in Python: The Complete Guide to for, while, and Loop Control Read More »
INTELEVO EP 04 – Complete Tutorial for AI & Data Science In this comprehensive guide: We explore how Python evaluates expressions through operator precedence. You’ll learn the complete precedence hierarchy, see step-by-step evaluations, and discover why parentheses matter. By the end, you’ll predict exactly how Python evaluates any expression you write. Table of Contents Introduction:
Expressions and Operator Precedence in Python Read More »