01. Introduction to Machine Learning Pipeline

PRDTM2-785 AI Trading C2 L1 Vid1 Intro

Course Overview: Preparing for Data Analysis

This course focuses on foundational steps prior to deploying machine learning models. Understanding these initial steps is crucial for effective data analysis.

Key Topics Covered:

  • Data Acquisition: Identifying and gathering relevant datasets based on a clear research question.
  • Data Pre-processing: Cleaning and formatting data to ensure compatibility with machine learning models.
  • Feature Engineering: Creating informative features that enhance the predictive power of models.
  • Exploratory Data Analysis: Analyzing data insights to guide model development.

The course lays the groundwork for more advanced topics, such as algorithm selection, model development, and model deployment, to be explored in subsequent courses.

Which of the following is the first step in the machine learning pipeline?
SOLUTION: Developing a question to answer.

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