Anastasia Smolskaya

Anastasia Smolskaya has extensive experience in the field of machine learning and data science. Anastasia is currently working as a Machine Learning Engineer at Inworld AI, starting in December 2021. Prior to that, they held the same position at Regula from February 2021 to December 2021. Before transitioning to a machine learning role, Anastasia worked as a Data Scientist at PandaDoc from March 2019 to February 2021. Anastasia also gained experience as a Machine Learning Engineer at Godel Technologies Europe from May 2018 to February 2019. Earlier in their career, Anastasia worked as a Data Scientist at LLC "Lifetech" (Turkcell Group) from September 2017 to April 2018. Anastasia also completed student practice at Otto-von-Guericke-Universität Magdeburg in 2016 and 2015. Overall, Anastasia has a diverse background in machine learning and data science, with experience in various industries.

Anastasia Smolskaya earned a Bachelor's degree in Computer Mathematics and Systems Analysis from Belarusian State University in the year 2017. Anastasia then pursued a Master's degree in the same field from Belarusian State University, which they completed in 2019. Prior to their studies at Belarusian State University, Anastasia also obtained a Bachelor's degree in Computer Mathematics from Otto-von-Guericke University Magdeburg, although the exact dates are not specified.

In addition to their formal education, Anastasia has acquired several certifications. These include "Understanding Docker" from Udemy, obtained in February 2020, "Sequence Models" from Coursera, obtained in February 2019, "Structuring Machine Learning Projects" from Coursera, obtained in December 2018, "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization" from Coursera, obtained in November 2018, "Convolutional Neural Networks" from Coursera, obtained in May 2018, "Neural Networks and Deep Learning" from Coursera, obtained in May 2018, "Математика и Python для анализа данных" from Coursera, obtained in February 2018, "Machine Learning Foundations: A Case Study Approach" from Coursera, obtained in September 2017, and "ML Course Open (Open Data Science Community) Top 100" from OpenDataScience, obtained in June 2017.