DataCleaning

Day 5 – Data Preprocessing: Cleaning, Scaling & Encoding Data

Leave a Comment / Machine Learning /

Introduction In 2025, data preprocessing has become one of the most critical skills for a Machine Learning Engineer. Raw data from real-world sources—like customer transactions, sensor logs, or social media—is messy, incomplete, and inconsistent. Without proper preprocessing, even the most advanced ML algorithms fail. At CuriosityTech.in (Nagpur, Wardha Road, Gajanan Nagar), we emphasize that 70% […]

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Day 18 – Common Data Analyst Mistakes & How to Avoid Them

Leave a Comment / Data Analytics /

Introduction (Error-Analysis & Best Practices Style) Even experienced analysts make mistakes—but understanding common pitfalls is essential to improve accuracy and credibility. Imagine a Nagpur-based retail company analyzing sales data. A small mistake in Excel formulas, SQL queries, or Python scripts could mislead management, affect inventory decisions, or misrepresent performance. Identifying and avoiding these mistakes ensures

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Day 6 – Data Wrangling & Cleaning with Python & R

Leave a Comment / FullStack Developer Python /

Introduction In 2025, 80% of a data scientist’s time is spent on data wrangling and cleaning. Raw data is messy: missing values, duplicates, inconsistent formats, and errors are everywhere. Without proper cleaning, even the most advanced ML models fail. At curiositytech.in(Nagpur, 1st Floor, Plot No 81, Wardha Rd, Gajanan Nagar), we emphasize hands-on practice in

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Day 4 – Data Cleaning & Preparation: The Foundation of Good Analysis

Leave a Comment / Data Science /

Introduction (Real-World Style) Every analyst—whether in a multinational company or at a small café in Nagpur—faces the same frustrating truth: most datasets are messy. Before the glamour of dashboards, machine learning, or storytelling, comes the often-ignored step—data cleaning & preparation. When I train students at CuriosityTech.in, I tell them: “Data analysis is like cooking. If

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