Stepping into Data Science - Predictive Analytics

Explore the fundamentals of data science and predictive analytics in this comprehensive conference talk. Delve into the core concepts of data science, its processes, and the types of questions it can address. Learn about the three essential skills required for data scientists and understand different categorization methods in machine learning. Discover the simplified machine learning process, focusing on classification techniques. Gain practical insights into feature engineering and data preparation for experiments using Python and Jupyter Notebook. Follow along as the speaker demonstrates how to create a training experiment and convert it into a predictive experiment, using the German Credit Data as an example. Master techniques for transforming categorical variables into binary dummy variables and rescaling numeric values to enhance your predictive models.

Intro
Technical Assistance
Agenda
What is Data Science?
What questions Data Science can answer?
Three essential skills of data scientists
Categorization - Way of conducting the learning
Supervised Model
Categorization - Machine Learning Techniques
Simplified Machine Learning Process
Classification
German Credit Data
Transform Categorical variables to Binary Dummy Variables
Rescale Numeric Values