This document provides an introduction to machine learning, including defining machine learning, describing the typical machine learning pipeline of data collection, model selection, and evaluation. It then gives several examples of machine learning applications, such as predicting house prices with regression, sentiment analysis with classification, document retrieval with clustering, and product recommendations with matrix factorization, dimensionality reduction, and deep learning. The document concludes by thanking the reader.

1. Machine Learning 101
Mauricio Vieira - http://mauriciovieira.net
September/2016

2. Who am I

3. Machine Learning
Pipeline

4. Data
Machine
learning
method
INtelligence
Pipeline

5. Case studies

6. Data
Machine
learning
method
INtelligence
Predicting House Prices

7. Data Regression INtelligence
Predicting House Prices

8. Sentiment analysis
Data
Machine
learning
method
INtelligence
Awesome feijoada, good
sides but awful service!

9. Sentiment analysis
Data Classification INtelligence
Awesome feijoada, good
sides but awful service!

10. Document retrieval
Data
Machine
learning
method
INtelligence

11. Document retrieval
Data INtelligenceClustering

12. Product Recommendation
Data
Machine
learning
methods
INtelligence
Past purchases
+ purchase
history of all
customers

13. Product Recommendation
Data INtelligence
Matrifx
factorization
Past purchases
+ purchase
history of all
customers

14. Product Recommendation
Data INtelligence
Dimensionality
reduction
Past purchases
+ purchase
history of all
customers

15. Visual Product Recommender
Data INtelligence
Machine
learning
method

16. Visual Product Recommender
Data INtelligence
Deep Learning

17. Process

18. Data
Machine
learning
method
INtelligence
Process
Task
Models &
parameters
Optimization
algorithm
evaluation

19. Thank you