Abstract: The Introduction to Machine Learning Workshop will build upon the attendee’s foundation of math and coding knowledge to develop a basic understanding of the most popular machine learning algorithms used in industry today. We will answer such questions as: What are the different types of ML algorithms ? What is Overfitting and how can we avoid it? Why is XGBoost consistently outperform other algorithms?
The first half of the session will include a discussion of both the theory and the implementation of Supervised modeling such as: Linear Regression, Logistic Regression, Decision Trees, Random Forest and XGBoost. We will then shift our focus to Unsupervised models including Clustering and Topic Modeling algorithms. This session will be interactive such that students will be able to develop their own models within the scope of the workshop.
Bio: Julia Lintern currently works as a Director of Data Science at Gartner. Previously, she worked as a Data Scientist for the New York Times. Julia began her career as a structures engineer designing repairs for damaged aircraft. Julia holds an MA in applied math from Hunter College, where she focused on visualizations of various numerical methods and discovered a deep appreciation for the combination of mathematics and visualizations. During certain seasons of her career, she has also worked on creative side projects such as Lia Lintern, her own fashion label.