Master Data Preprocessing, Wrangling, and Cleaning for Machine Learning Projects!

Data preprocessing is a vital step in any machine learning workflow. In this tutorial, we’ll guide you through the essential steps to clean, wrangle, and preprocess data to ensure your machine learning models are accurate and reliable. What you’ll learn in this video: ✔️ The importance of data preprocessing in machine learning ✔️ Handling missing and inconsistent data ✔️ Techniques for data wrangling and transformation ✔️ Data cleaning tips to improve model performance ✔️ Real-world examples to prepare datasets for machine learning 💡 Whether you're a beginner or an advanced data scientist, this video will help you build robust pipelines for cleaner, high-quality datasets. 📌 Don’t forget to like, comment, and subscribe for more tutorials on machine learning and data science! #DataPreprocessing #DataWrangling #DataCleaning #MachineLearning #DataScience #PythonTutorial #DataPreparation #MLWorkflow #DataEngineering #codanics #urdu #babaammar #aammartufail #pakistan #urduai #pythonkachilla You can book One to one consultancy session with me on Mentoga: https://mentoga.com/muhammadaammartufail #codanics #dataanalytics #pythonkachilla #pkc24 ✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅ Python ka chilla 2024 You can now register for Python ka chilla 2024 This is a paid course which you can register and find more information at the following link: https://forms.gle/kUU3eZJsFRb7Cn6r8 ✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅ Here you can access all the codes and datasets from Python ka chilla 2024: https://github.com/AammarTufail/python-ka-chilla-2024 ✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅ --------------------------------------------------------------------------------------------------------------------------------------- --------------------------------------------------------------------------------------------------------------------------------------- 1. MS Excel: 1. https://www.youtube.com/playlist?list=PL9XvIvvVL50G7D7_4ZDNAlS9JczrG57L6 2. https://www.youtube.com/playlist?list=PL9XvIvvVL50Hl4kVygAWYEpBXUteQlAiN 2. ABC of Statistics for Data Analytics and Data Understanding: 1. https://www.youtube.com/playlist?list=PL9XvIvvVL50FftePmir6RYd9r378DCQda 2. https://www.youtube.com/playlist?list=PL9XvIvvVL50H2YCvuZklqjBiqsJt_0KWI 3. Free Ebook written in Roman Urdu: 1. https://codanics.com/books/abc-of-statistics-for-data-science/ 3. Mathematics for Data Analytics and Data Understanding: 1. https://www.youtube.com/playlist?list=PL9XvIvvVL50EFb5DokvHbunW6AsLtdMXh 2. https://www.youtube.com/playlist?list=PL9XvIvvVL50G3-_NMFreX72zbICK9-NW- 4. Power BI for Data Visualization 1. https://www.youtube.com/playlist?list=PL9XvIvvVL50GTwV7dqdBKxsFs7WYzlOYZ 5. Tableau for Data Visualization 1. https://www.youtube.com/playlist?list=PL9XvIvvVL50F5_vuj1805AMxpAms9HT6- 6. SQL (Structured Query Language) 1. https://www.youtube.com/playlist?list=PL9XvIvvVL50FszjOhcZw9WXIJQY6ZwV5g 7. Python for Data Analytics and Data Science 1. The whole python ka chilla for data science (Free main) is at this link: https://shorturl.at/vxGZ8 8. R programming: 1. Complete course on R is here: https://codanics.com/courses/r-with-aammar/ 9. Bonus Complete Course on AI and Data Science: 1. Six months AI and Data Science Mentorship program is uploaded here: https://codanics.com/courses/six-months-of-ai-and-data-science-mentorship-program/ 10. Markdown Language to Make Data Reports: 1. https://youtu.be/qJqAXjz-Rh4 Please share and like this video, also write your comment here and subscribe our channel. --------------------------------------------------------------------------------------------------------------------------------------- ✅Our Free Books: https://codanics.com/books/abc-of-statistics-for-data-science/ ✅Our website: https://www.codanics.com ✅Our Courses: https://www.codanics.com/courses ✅Our YouTube Channel: www.youtube.com/@Codanics ✅ Our whatsapp channel: https://whatsapp.com/channel/0029Va7nRDq3QxRzGqaQvS3r ✅Our Facebook Group: https://www.facebook.com/groups/codanics ✅Our Discord group for community Discussion: https://discord.gg/QpvUKEtUJD ✉️For more Details contact us at [email protected] Chapters: 00:00:00 What is Data Pre-processing? 00:30:27 Steps in Data Pre-processing 00:37:49 What are Outliers? 01:00:13 Types of Outliers 01:10:01 How to Identify Outliers? 01:23:25 Z-score methods for Outliers 01:29:30 Handling Outliers 01:34:23 Outliers, Final Words 01:39:04 Removing Outliers in Dataset Example 01:55:29 Missing Values k Rolay 02:12:03 Imputing Missing Values Basic to Advance Methods 03:07:04 Data Scaling and Normalization 03:28:46 Feature Scaling 03:27:48 Tips about Feature Scaling 03:40:40 Data Scaling and Pre-processing in Python 03:59:20 Data Transformation in Python 04:04:16 Data Normalization in Python 04:15:22 Most Used Scalar Types 04:16:06 What is Feature Encoding? 04:29:11 Why feature encoding is needed? 04:41:55 Feature Encoding in Python