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Ayodeji's data science portfolio

  • Created a tool that estimates data science salaries (MAE ~ $ 11k) to help data scientists negotiate their income when they get a job.
  • Scraped over 1000 job description from glassdoor using python and selenium
  • Engineered features from the text of each job description to quantify the value companies put on python, excel, aws, and spark.
  • Optimised Linear, Lasso, and Random Forest Regressors using GridsearchCV to reach the best model.
  • Built a client facing API using flask

For this example project I built a ball classifier to identify balls from different sports. This could be useful for someone who is new to sport from a certain country. They could take a picture of a ball and an app could serve them some information about the history and rulesof the game. This is the underlying model for building something with those capabilities.

I was able to get the model to predict the sport of the ball with 94% accuracy after minimal tuning. For most of the cases this would meet the needof an end user of the app. To get these results I used transfer learning on a CNN trained on resnet34.This create time efficiencies and solid results.

  • built a model for fraud prevention.
  • built another project for risk analytics;
  • analysed over a thousand customer behavior for a cetain product which in turn is used for the improvement of the product.

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Ayodeji's data science portfolio

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