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Day 1 – ML Foundations & Spark Introduction

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  5. Day 2 – Supervised Learning: Regression
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Section outline

►Day 2 – Supervised Learning: Regression

    • ML vs Statistics vs Data Science

    • Data Preprocessing: Encoding, Missing Values, Outliers

    • Python and R for ML: NumPy, Pandas, ggplot2

    • Spark Basics: RDD, DF, SparkR, MLlib

    • Lab: S&P 500 stock data analysis

►Day 2 – Supervised Learning: Regression

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