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