Basic Machine Learning for Developers

1. Basic Machine Learning
for Developers
@ignacio_elola

2. What is import

3. Who I am
Ignacio Elola
Background:
● Theoretical Physics
● Complex / Stochastic Systems
Current Obsessions:
● Web Data
● Data Science for Business
● Growth

4. What is ML
Arthur Samuel (1959). Machine Learning: Field of study that gives computers
the ability to learn without being explicitly programmed.
Tom Mitchell (1998) Well-posed Learning Problem: A computer program is
said to learn from experience E with respect to some task T and some
performance measure P, if its performance on T, as measured by P, improves
with experience E.

5. What is ML
- Spam detection
- Credit Card Fraud
- Medical diagnosis
- Sentiment analysis
- Recommendation systems

6. What is ML
Dataset:
● Train set
● Test set

7. What is ML
Supervised Learning
Unsupervised Learning
Reinforcement Learning

8. ML
Categorization by output:
classification
regression

9. ML
Do I want to predict a category?
or
Do I want to predict a number?

10. ML - Regression
Some algorithms:
Least Squares
Lasso
Support Vector Regression

11. ML - Regression
Least Squares

12. ML - Regression
Support Vector Regression

13. ML - Classification
Can be divided in two groups of algorithms, whether we
have labeled data or not
With labeled data:
KNeighbours classifier
SVC
Without:
KMeans
MeanShfit

14. ML - Live Demo
Link to the code used in the live demo:
https://github.com/ignacioelola/ML-examples

15. Resources
- O’Reilly books (Doing Data Science, Data
Science for business)
- For Python: sklearn
- ML course on coursera
- Kaggle competitions

16. Thank you!