The concept of data mining refers to the process of discovering the facts and relationships contained in a data set. Machine learning algorithms, as part of what is known as Artificial Intelligence (AI), aim to analyze these data sets to be able to be later applied in predictions or classifications, just to mention a couple of examples.
This analysis and its implications are changing the way we interpret the world and relate to it, and more and more sectors of the industry depend on them. In fact, the applications of Machine Learning are as numerous as they are impressive in our daily lives: from product recommenders to the development of autonomous vehicles, through sales predictors, image classifiers or text analyzers (“sentiment analysis”).
In this "Introduction to Machine Learning" course the concept of algorithm, its types and its main applications will be covered, also reviewing concepts and associated scenarios of increasing importance: Deep Learning, computer vision, text analysis and Internet of Things (IoT).
To attend this course attendees must know the Python programming language.
Content:
- Introduction to Machine Learning
- Algorithms
- Nomenclature
- Algorithm classification
- Training and overtraining
- Error functions
- Validation of a model
- Programming languages and environments
- Big data
- Neural Networks
- Applications
- Deep learning
- Artificial vision
- Natural Language Processing
- Internet of Things (IoT)
