Data cleaning with python for Data analytics and Modeling
Data cleaning with python for Data analytics and Modeling: Master the Art of Data Cleaning, Transformation, and Preparation for Robust Analytics and Machine Learning Models by Ahmed Khorshid
English | December 26, 2024 | ISBN: N/A | ASIN: B0DRNQYTHV | 190 pages | EPUB | 4.25 Mb
English | December 26, 2024 | ISBN: N/A | ASIN: B0DRNQYTHV | 190 pages | EPUB | 4.25 Mb
In the world of data science, clean data is the foundation of accurate analysis and reliable machine learning models. "Data Cleaning with Python" is your ultimate guide to mastering the essential techniques and tools for preparing data for analytics and modeling. Whether you're a data analyst, data scientist, or machine learning engineer, this book equips you with the skills to handle messy, incomplete, and inconsistent datasets with confidence.
This comprehensive guide covers everything from the basics of data cleaning to advanced techniques, including handling missing data, removing duplicates, detecting outliers, and transforming data for machine learning. With practical examples, step-by-step tutorials, and real-world case studies, you'll learn how to use Python's powerful libraries like Pandas, NumPy, Scikit-learn, and OpenRefine to clean and preprocess data efficiently.
Key Features:
- Step-by-Step Tutorials: Learn how to clean and preprocess data using Python with hands-on examples.
- Real-World Case Studies: Apply your skills to real-world datasets, including the New York City Airbnb dataset and the Titanic dataset.
- Advanced Techniques: Master advanced data cleaning techniques like text cleaning, date and time handling, and categorical data encoding.
- Automation and Best Practices: Discover how to automate data cleaning workflows and follow best practices for reproducible and scalable data preparation.
- Tools and Libraries: Explore Python's ecosystem of data cleaning tools, including Pandas, NumPy, Scikit-learn, and OpenRefine.