Nodar is a Data Scientist with a strong software development background in Python, advanced analytics algorithms, tools and technologies - embracing big data, obsessing over performance and scalability, and striving to deliver insights and recommendations as fast as possible. He leverages the latest techniques in machine learning across computer vision, sentiment analysis and recommendation systems to optimize decision-making.
Design and build production-level machine learning systems for clients across different industries.
Prepare documentation, reports, and visualizations to communicate complex data/analyses to users.
Identify, research, interpret, group, source, manipulate, and enrich multiple structured and unstructured data assets to facilitate effective analytics.
Developed and deployed an anomaly detection and similarity measure solution for analyzing time series data.
Identified, collected, and filtered data between several unequal-length time series.
The solution focuses on anomaly detection and similarity assessment.
Education
1. Python (Advanced)
2. SQL (Advanced)
HackerRank
2020 - 2020
1. Advanced Python
2. Scaling Python Data Applications with Dask
Pluralsight
2020 - 2020
Doctor of Philosophy Computational Linguistics
Georgian Technical University
2019 - Present (6 years)
1. Machine Learning A-Z™: Hands-On Python & R In Data Science
2. Data Science A-Z™: Real-Life Data Science Exercises Included
3. Deep Learning A-Z™: Hands-On Artificial Neural Networks
4. Data Visualization on the Browser with Python and Bokeh
5. Interactive Python Dashboards with Plotly and Dash
6. The Complete SQL Bootcamp
Udemy
2018 - 2019 (1 year)
Master's Degree in Economics
International School of Economics at Tbilisi State University