Kashu Yamazaki

Kashu Yamazaki

Research associate, Electrical Engineering and Computer Science, University of Arkansas, Fayetteville

Applied Machine Learning Intensive

Teaching Assistant, University of Arkansas and Google, 2021

Class Overview

Summary: A bootcamp-style course for undergraduate college students. Designed for students who weren’t necessarily majoring in computer science, the goal was to enable participants to apply machine learning to different fields using high-level tools.

People

Instructor:

Khoa Luu

Instructor:

Thi Hoang Ngan Le

Instructor:

Chase Rainwater

Instructor:

Shengfan Zhang

Lecture Information

Duration: June 7 ~ July 30 (Mo,Tu,We,Th,Fr) 8:45am-3:45pm (CST)

Codes: applied-machine-learning-intensive

Grades

90-100 : A 80-89 : B 70-79 : C 60-69 : D <60 : E

Drill Sessions

Time: 9:45-11:15am and 1:30-3:45pm
Location: BELL 1108E

Capstone Projcts

2-4 of the AMLI students will be assigned to the project during the last 4-5 weeks of the program. The students will apply their new found ML skills to the project. Part of the project titles are listed below:

  • Stock Price Prediction
  • Cybersecurity: Network Threat Detection
  • Action recognition
  • Predicting the Risk of a Health Problem
  • UARK Car Detection and Car Type Identification
  • Face Detection & Recognition
  • UARK campus scene understanding

Lecture Topics

  • week1 - (June 7 ~ June 11)

Summary: python basics, probability and statistics, linear algebra, machine learning introduction, machine learning fairness

  • week2 - (June 14 ~ June 18)

Summary: data visualization, exploratory data analysis

  • week3 - (June 14 ~ June 18)

Summary: regression, neural networks

  • week4 - (June 28 ~ July 02)

Summary: classification, image classification, image-video classification, saving/loading models

  • week5 - (July 05 ~ July 09)

Summary: deep learning, CNNs, RNNs, NLP, transfer learning

  • week6 - (July 12 ~ July 16)

Summary: clustering, k-means, embedding, decision tree, random forest, KNN, SVM, Bayesian, XGBoost

  • week7 - (July 19 ~ July 23)

Summary: advanced activation fuctions, Big O, dimensionality reduction, loss functions, regular expressions

  • week8 - (July 26 ~ July 30)

Summary: career development, interview preparation, capstone presentation

Sponsers

Media Coverage

College of Engineering Offers Applied Machine Learning Intensive for Summer