Name: Miguel Novo Villar
Type: User
Company: Atomic Maps - University of Rochester
Bio: Data scientist interested in Big Data (Spark), Machine Learning, Deep Learning and Predictive Analytics.
Twitter: miguelnovovil
Location: United States & Spain
Miguel Novo Villar's Projects
Analysis of Meta-Communities Surrounding “Roe v. Wade” on Reddit: Graph Analytics.
Analyze where Accidents happen and Predict where accidents are likely to happen (Upcoming)
This project seeks to explore the frequent line-ups of successful & unsuccessful clubs constrained by finances. To investigate this problem, the researchers (1) built a game week over game week linear optimized model, (2) used actual club squad rosters, and conducted (3) dissimilarity analysis by drawing a network exhibiting the distance between maximized frequent itemsets and minimized itemsets.
Premier League (Soccer) Player Optimization
Congressional Tweet Classification (D or R). Logistic regression technique that exhibited 75% percent accuracy.
NLP model to classify Tweets by country and allocate topics with Latent Dirichlet Allocation techniques.
Classify credit risk as good or bad based on different parameters. Logistic Regression Model.
course materials for Data Science at Scale
Final Project for dscc202-402-spring2022
End-To-End Data Intensive Appplication: Token Recommender on the Ethereum Blockchain (ERC-20 Tokens). Spark & Databricks
Tutorial on geospatial data manipulation with Python
New York State Public Schools Graduation Rates: Predicting Success. Statistical Machine Learning.
This is the github repo for Learning Spark: Lightning-Fast Data Analytics [2nd Edition]
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Config files for my GitHub profile.