Data Preparation 101 for Machine Learning Model Building

Опубликовано: 01 Январь 1970
на канале: AIEngineering
5,094
112

About the Session:

This is an interactive Live Session on Data Preparation 101 where we will learn the following topics.
• What is Data Preparation and Why do we Need it
• Data Pre-processing, Wrangling
• Handling Duplicate Values, Missing Values, Imbalance Datasets, etc.
• Outlier Analysis and Removal
• Feature Encoding: Encoding the categorical data
• Extracting Input and Target Variables
• Data Partitioning - Splitting into Train and Test
• Feature Transformations - Normalisation, Standardisation & Scaling

About the Speaker:

Aarthi is currently working as a Lead Data Scientist at Allianz Belgium where she applies Data Science for solving Sales and Marketing problems in the Insurance sector. She is an ex-entrepreneur who has hands-on experiences in business intelligence, machine learning, and deep learning. We thank her for giving us a chance to learn through her and her experiences.

This Live Session is a part of the ongoing Machine Learning Bootcamp at DPhi.

If you had not registered for it, feel free to do so by following this link and selecting the most suitable track for you: https://bit.ly/MLBootcamp-Registration2

Connect with the speaker-
Aarthi Kumar:   / aarthikumar  


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