Preparing for Data Analysis

We'll define the steps of the machine learning pipeline, from data ingestion to production. We'll emphasize preprocessing and feature engineering, essential steps to well-performing trading models.

How do you get data from the Internet to your model? We'll talk about ingestion, transformation,and data wrangling using Pandas, the industry-standard time-series package for data manipulation.

Feature engineering significantly improves model performance, and in this lesson, we'll go over strategies you can use. Basic and more involved techniques will be presented, with use cases noted.

What's your data trying to tell you? Use EDA, exploratory data analysis, to find out! We'll use Python's two most popular plotting packages, matplotlib and Plotly, to find out your data's secrets.