Preparing Financial Data for Machine Learning

Overview

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This course explores the essential steps for preparing data for machine learning, focusing specifically on financial time series data. From feature engineering to scaling and train-test splitting, you will learn to apply best practices in preprocessing data to pave the way for successful model training and evaluation.

Syllabus

Lesson 1: Feature Engineering for ML
Lesson 2: Scaling Features with StandardScaler
Lesson 3: Splitting Dataset into Training and Testing Set
Lesson 4: Addressing Data Leakage in Time Series
Lesson 5: Creating Lag Features for Time Series Prediction

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