Inspiration

Super interested in Machine Learning and data analysis

What it does

Forecasting stock growth

How we built it

  • Analyse the dataset first
  • Go with baseline code
  • Try grouping features
  • Feature Engineering by each team member
  • Feature selection
  • Model selection
  • Grid search for tuning parameters

Challenges we ran into

  • Analyse baseline code
  • New ideas but hard to implement
  • Sleep deprivation :[

Accomplishments that we're proud of

  • Tried different models on a real-life problem
  • Got a relatively good improvement for the baseline

What we learned

  • Have a deeper understanding of data analysis
  • Various classification machine learning algorithms for Stock Prediction

What's next for Stock Prediction GOGOGO

  • Digging deeper into relationships from raw data
  • Neural Networks
  • For those tested models, find different ways to tune parameters

_More details are on Github

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