Anastasiia Kornilova

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MS in applied mathematics, data scientist(5 years of experience), lecturer, speaker, online education fan. My professional interests include deep learning, natural language processing, recommendation systems and scalable data science solutions. Author of "Intro to Data Analysis and Inferential Statistics with R" course on Prometheus (Ukrainian Coursera) http://courses.prometheus.org.ua/courses/IRF/Stat101/2016_T3/about Self-learner: successfully finished 20+ MOOCs. Author of two blogs: http://energyfirefox.blogspot.com/ — in Ukrainian, about data science and online learning http://datascientistdiary.blogspot.com/ in English, mostly about deep learning and NLP.

data science word2vec nlp healthcare kaggle deep learning neural networks autoencoder recommender systems

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Anastasiia Kornilova

Präsentationen

Mahout

Recommender systems

MapReduce Design Patterns

Stay well with machine learning

Neural Networks and Deep Learning

Kaggle - global Data Science community

NLP approach for medical translation task

Introduction to Data Science

Gefällt mir

CRISP-DM: a data science project methodology

Data science and pending EU privacy laws - a storm on the horizon

Introduction to ML with Apache Spark MLlib

Value of Prototyping

NLP approach for medical translation task

Big Data - Big Pitfalls.

Implementing Click-through Relevance Ranking in Solr and LucidWorks Enterprise

Recommender Systems (Machine Learning Summer School 2014 @ CMU)

Agile Data Science by Russell Jurney_ The Hive_Janruary 29 2014

A Statistician's View on Big Data and Data Science (Version 1)

Spark!

Applying Machine Learning to Network Security Monitoring - BayThreat 2013

Data Mining With R

R journal 2010-2