We propose a list of publications on a series of topics for your final presentation. Choose a paper of your interest and prepare a few slides and a short presentation of 10 min describing the main ideas of the paper you chose. You may prepare and present in pairs.
The goal is for you to be able to understand and synthesize technical publications in fields that use machine learning tools.
Make a presentation of a few slides describing the paper of your choice that is 8 minutes long and 2 min questions.
We will time the presentations.
If you have a group of 3 people, the presentation can last 12 minutes.
Every member of a group has to speak in the presentation, ideally for 4 minutes.
Make your presentation in Google Slides and send us a link. Please, don’t use PowerPoint, it is not compatible with Linux in the computers we use.
Students from the morning session have to send us their presentations by 8am. The students from the afternoon session have to send us their presentation links by 6pm. Your group cannot present if you don’t send us the slides by the indicated time.
We will evaluate your presentation based on the following aspects.
- Description of the problem being addressed in the paper.
- Importance of the addressed problem.
- Machine learning model description.
- Evaluation metric of choice.
- Experimental results.
Read through the following list of proposed topics and publications. When you are ready and have selected a paper, follow this link and write your name and your partner’s next to your choice. Choosing a paper is a first come, first served assignment; you may not choose a paper that is no longer available.
You have until Thursday July 04th 23:59 to select a paper. If you don’t make your selection by the specified date, we will assign you a paper and a partner.
- A data-driven, machine learning framework for optimal pest management in cotton
- Machine learning methods for crop yield prediction and climate change impact assessment in agriculture
- Using Deep Learning for Image-Based Plant Disease Detection
Climate Change and Conservation
- Application of Deep Convolutional Neural Networks for Detecting Extreme Weather in Climate Datasets
- Climate Change and Power Security: Power Load Prediction for Rural Electrical Microgrids Using Long Short Term Memory and Artificial Neural Networks
- Exploiting Data and Human Knowledge for Predicting Wildlife Poaching
- Machine Learning to Analyze the Social-Ecological Impacts of Natural Resource Policy: Insights from Community Forest Management in the Indian Himalaya
- Predictive segmentation of energy consumers
- Customer segmentation of multiple category data in e-commerce using a soft-clustering approach
- Learned lessons in credit card fraud detection from a practitioner perspective
- Machine Learning for User Modeling
Health Care and Epidemology
- An unsupervised machine learning model for discovering latent infectious diseases using social media data
- Is Demography Destiny? Application of Machine Learning Techniques to Accurately Predict Population Health Outcomes from a Minimal Demographic Dataset
- Prediction of In-hospital Mortality inEmergency Department Patients With Sepsis:A Local Big Data–Driven, Machine LearningApproach
- Rodent reservoirs of future zoonotic diseases
- Using Machine Learning Classifiers to Assist Healthcare-Related Decisions: Classification of Electronic Patient Records
- A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes
- From Empirical Analysis to Public Policy: Evaluating Housing Systems for Homeless Youth
- Working women and caste in India: A study of social disadvantage using feature attribution