Collection of notebooks on machine learning topics: Introduction to Python and Numpy Classification: kNN, Logistic regression, Support Vector Machines Regression: kNN, Least Squares, Bayesian Inference, Gaussian Processes Clustering: k-means, Spectral Clustering Topic Modeling Most of the notebooks above rely on
Applications of Machine Learning
Here you can find material of some of my courses https://github.com/vgverdejo/Applications-of-Machine-Learning 3 forks. 3 stars. 0 open issues. Recent commits: Update README.md, GitHub Update README.md, GitHub Merge branch 'master' of https://github.com/vgverdejo/Teaching-activities, Vanessa Gómez Verdejo actualizando feature selection, Vanessa Gómez Verdejo
Graph visualization
Heatmap Visualization
Data visualization
Now that Big Data technologies have enabled the processing of huge amounts of data, the next step is to present the processed data in a clear and efficient way. Being aware of this necessity, the ML4DS group has integrated machine
Web crawling
During recent years the Internet has become an important source of information, able to provide data for any machine learning task. To take advantage of this fact, the ML4DS group has developed tools for the exploration of web domains. These
Recommender Systems
Amazon, Spotify, Netflix, YouTube… most e-commerce companies and content providers incorporate recommender systems to their platforms. This way, they are able to recommend to each user products that they could potentially find interesting, increasing the user’s expertise and the company’s