T11 - Machine Learning

13 Dezembro 2019, 13:00 • Sara C. Madeira

What is Machine Learning ? 

Why use Machine Learning ? 

Types of Machine Learning Systems

- Supervised versus Unsupervised versus Semisupervised versus Reinforcement Learning

- Batch and Online Learning

- Instance-Based Versus Model-Based Learning

Main Challenges of Machine Learning 

- Insufficient Quantity of Training Data

 - Non-representative Training Data

 - Poor-Quality Data

 - Irrelevant Features

 - Overfitting/Underfitting the Training Data

 Testing and Validating

T10 - Data Mining

6 Dezembro 2019, 13:00 • Sara C. Madeira

Data Mining: Overview.

Data Mining Concepts and Techniques: Introduction.

- Why Data Mining?  

- What Is Data Mining?

- What Kinds of Data Can Be Mined? 

-  What Kinds of Patterns Can Be Mined? 

-  Which Technologies Are Used? 

- Major Issues in Data Mining

Not Taught.

29 Novembro 2019, 13:00 • Sara C. Madeira

Lesson not teached due to a conference.

S3 - 2

22 Novembro 2019, 13:00 • Maria Isabel Fraga Alves

Exploratory Data Analysis: Basic tools of R in RStudio. A Case Study with a dataset: one (simulated) day's worth of ads shown and clicks recorded onthe New York Times home page in May 2012

S3 - 1

15 Novembro 2019, 13:00 • Maria Isabel Fraga Alves

Statistical Thinking in the Age of Big Data