Data And Features, Understanding Datasets, 02A

🚀 Course: Machine Learning for Beginners 🔁 Module 02: Data And Features 🧠 Lecture A: Understanding Datasets 👇 Link to the notebook: https://tinyurl.com/2ymo9n5f 🚀 Machine learning dataset basics for beginners: understand tabular data structure, features, and target columns so you can design better ML datasets and spot problems early. This lecture-style tutorial explains rows as cases, feature engineering with numeric, categorical, and text data, and how target variables define regression vs classification tasks. You will also learn data quality checks, including detecting missing values, placeholder codes, outliers, sampling bias, and skewed customer churn datasets using Python and pandas. Watch to build a solid foundation in dataset design, data types, and basic data cleaning before training machine learning models. ▶️➕🔔 Don't forget to like, subscribe, and hit the notification bell! ⚠️ Disclaimer: AI Voice used. #tutorials, #pandas, #missingdata, #datacleaning, #samplingbias, #syntheticdata, #pandas,