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"Do what you can, with what you've got, where you are."- T.R.
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"Do what you can, with what you've got, where you are."- T.R.
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aig3rim/README.md

Hi, I'm Aigerim πŸ‘‹

γ“γ‚“γ«γ‘γ―γ€€πŸŒΈ

I'm an engineer turned data scientist who loves finding insights from data. I strongly believe that by having a better understanding of data and applying machine learning algorithms we can make the world a better place.

Currently, I'm a Data Scientist at Rakuten helping various external clients to make a better business decisions through providing insights. In my free time, I enjoy learning new things and sharing my knowledge through my blog posts.

Outside of work, I also...

  • πŸ“ Write about data science, machine learning and marketing
  • πŸƒβ€β™€οΈ Run 7-8 km 3 times a week
  • πŸ“š Read about cognitive & social psychology, enjoy classic and contemporary literature
  • 🐢 Walk and go to dog parks with our dog Taquito
  • 🌱 I'm currently learning/improving knowledge in statistics & probability, deep learning, story-telling

Find me around the web 🌎:

Linkeidn Batch Medium Batch

Pinned

  1. Anomaly_detection_using_ML Anomaly_detection_using_ML Public

    Price anomaly detection for time series using K-means clustering, Isolation Forest, One Class SVM and Gaussian Distribution

    Jupyter Notebook 2 2

  2. AB_test_analysis AB_test_analysis Public

    Understanding results of A/B test run by e-commerce website using p-value calculations, z-core test, logistic and multiple linear regressions and bootstrapping sampling distribution

    HTML

  3. Churn_prediction_using_logistic_regression Churn_prediction_using_logistic_regression Public

    Predicting customer churn with logistic regression by applying Synthetic Minority Oversampling Technique and Recursive Feature Elimination

    Jupyter Notebook 2

  4. Disaster_response_pipeline Disaster_response_pipeline Public

    ML pipeline to categorize emergency messages using NLTK and visualize the results with Flask

    Jupyter Notebook

  5. Customer_segmentation_Arvato Customer_segmentation_Arvato Public

    k-means clustering, XGBClassifier and Gradient Boosting for customer segmentation and acquisition

    HTML 2 3

  6. Predict_CLTV_with_linear_regression Predict_CLTV_with_linear_regression Public

    Utilize linear regression to predict Customer Lifetime Value and develop positive ROI strategies

    Jupyter Notebook 8 6