Data Cleansing Master Class in Python
The Complete Guide to Data Cleansing for Machine Learning Engineers
Created by Mike West
Explore practical data cleansing techniques tailored for machine learning projects using Python. You will gain hands-on experience with data imputation, advanced cleaning methods, and strategies to prepare your data for accurate modeling.
Packt | Dec 2021 | 213 min
What You Will Learn
You will work through interactive Python examples that guide you step by step. By applying each technique directly to sample datasets, you will build confidence in transforming raw data into a model-ready format. The focus is on learning by doing, so you will practice every concept as you go.
Key Features
- Apply real-world data cleansing to improve dataset quality and reliability
- Master advanced techniques to handle missing, inconsistent, or noisy data
- Prepare data to prevent leakage and ensure trustworthy model evaluation
Target Audience
Ideal for machine learning engineers and data scientists who already know Python and basic machine learning concepts. If you want to strengthen your data preparation skills and ensure your models are built on clean, reliable data, this course will help you reach that goal.
