Machine Learning Systems
Students will learn how to explore new data sets, implement a comprehensive set of machine learning algorithms from scratch, and master all the components of a predictive model, such as data preprocessing, feature engineering, model selection, performance metrics and hyperparameter optimization.
Regression, Classification, Data Preprocessing, Model Evaluation and Ensembles
Dimensionality Reduction, Clustering, Association Rules, Anomaly Detection, Network Analysis and Recommender Systems
Amazon Web Services, Apache Stack (Spark, Kafka, Cassandra), Elasticsearch and Docker
Machine Learning with R, Neural Networks, Natural Language Processing, and Data Visualization with D3.js