Next Meetup

HML Study Session #4
1. Machine Learning Fundamental Course: Statistical Learning, via Stanford University online [1]. In this session, we continue our discussion of statistical learning with resampling techniques, which is based on chapter 5 of ISLR course and book. We will learn how to extract actionable insights from these chapters, to tackle various issues in a typical ML workflow. Topics include cross validation, bootstrap, and best practices for resampling. 2. Deep Learning Specialization, via Coursera [2]. We are now on the 2nd course of DL specialization series, i.e., Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization. In this session, we will talk about the materials discussed in the 1st week of the series. Discussion topics include bias, variance, regularization and gradient checking implementation. Checkout the previous discussion topics on our website [3] Whether you are new- or experienced ML enthusiasts, these courses will help equip you with ML fundamentals, strengthen your statistical reasoning, and streamline your data analysis and model building pipeline. So, come join us for either or both study sessions. The only pre-requisite is, your curiosity! (e.g., come with 1 question/topic for discussion). Links: [1] [2] [3]

University of Hawaii POST Building

1680 East West Road · Honolulu, HI

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We are students, scientists, engineers, entrepreneurs, and everyday people who are interested in data science, machine learning, artificial intelligence. Our goal is to promote an interest in Machine Learning & Artificial Intelligence and increase the adoption of these technologies in Hawaii.

Edit 06/08/18: We are changing venue and meeting times. Please take the time to fill out the following 5-question survey (expected duration is 5 minutes). Your responses will help us better organize this meetup.

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