This repository holds our machine learning projects. Here, two Jupyter Notebooks were created for further analyses on some data. One of them is related to air pollution, which may be considered the most significant impact upon human evolution. Through time, treaties and protocols, such as Kyoto and Paris agreements, were created focused on reducing gas emission, a major cause of the Greenhouse Effect. With the advance of Machine Learning, today is possible to predict events to reduce pollution effects. Hence, this Jupyter presents a study of Regression Models to predict continuous variables related to air quality features.
The second Jupyter analyzes Bitcoin. This cryptocurrency has revolutionized money in our world. Cryptocurrency is a virtual currency based in blockchain, a distributed system in which transactions are made in an intriguing safety due to its decentralized, untraceable, and immutable aspects. Recently, ransomware attackers have evolved the way they charge to unlock attacked systems, asking for cryptocurrency as payment. As blockchain is hard to track, this study aims to analyze how transactions take place and try to predict if a crypto coin - in this case, Bitcoin - the address is being used for malicious intent or not.
The data used on all of the projects are founded on this website: UCL Machine Learning Repo.
To execute the jupyters notebooks, you need first to install the prerequisites (founded below). Next, run jupyter on your notebook with
$ jupyter notebookAnd when in browser, execute all cells. It can also be executed in Colab.
Before you start, you'll need to download and install the following tools:
These are the following tools used in this project:
The projects were developed in conjunction with the discipline developed by prof. Diego Furtado from Federal University of São Carlos.
Authors
 Felipe Tavoni |
 Reynold N. Mazo |