Predict Macro Economic Trends using Kaggle Financial Dataset

In this machine learning project, you will uncover the predictive value in an uncertain world by using various artificial intelligence, machine learning, advanced regression and feature transformation techniques.

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Project Template Outcomes

  • Understanding the problem statement
  • Importing the Train and Test dataset directly from the source
  • Performing basic EDA
  • Checking for null values and making imputations using appropriate methods
  • Dropping rows with null values
  • Understanding how a Linear model works and underlying assumptions
  • Multicollinearity, Autocorrelation, linearity and Normal distribution
  • Applying Ridge Regression for training
  • Applying GLMnet model for training
  • Applying elasticnet model for training
  • Converting Dataframe into DMatrix
  • Applying XGBoost model for making predictions
  • Defining parameters for XGBoost
  • Defining evaluation metrics
  • Plotting graphs for the results obtained to select the best model
  • Making final predictions with the best-selected model

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Project Description

Two Sigma is a technology company dedicated to finding value in the world’s data. Since its founding in 2001, Two Sigma has built an innovative platform that combines extraordinary computing power, vast amounts of information, and advanced data science to produce breakthroughs in investment management, insurance, and related fields. Economic opportunity depends on the ability to deliver singularly accurate forecasts in a world of uncertainty.

By accurately predicting financial movements, you will learn about scientifically-driven approaches to unlocking significant predictive capability.

Two Sigma is excited to find predictive value and gain a better understanding of the skills offered by the global data science crowd.

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