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sklearn-estimator

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Developed a model using Random Forest algorithm to get prediction of user defined number of stocks to go long & short in all trading sessions of upcoming year. Achieved 14.04% CAGR with 100% profitability in all seven years of backtested data. The model outperformed the index in 5 years out of the total 7 years of testing.

  • Updated Oct 20, 2022
  • Jupyter Notebook

The aim of this project is to classify the faces. Olivetti Faces dataset has been used. In this dataset there are ten different images of each of 40 distinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions (open / closed eyes, smiling / not smiling) and facial details (glasses / no …

  • Updated Nov 26, 2019
  • Jupyter Notebook

Sales and pricing data that is subject to noise and skewness are managed with difficulty thanks to the Copper Industry Sales and Leads Prediction Project. In the industry, manual forecasts can be inaccurate and time-consuming. The creation of machine learning models is the main goal of this project in order to overcome these obstacles.

  • Updated Dec 17, 2023
  • Jupyter Notebook

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