Projects made for the course SCC0230 Artificial Intelligence using concepts like knowledge graphs and classification.
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The projects are intended for the course SCC0230 - Artificial Intelligence, at ICMC - USP, 2nd semester of 2020. The subjects treated were:
'History of AI. Characterization of AI problems. Some AI applications: PLN, robotics, etc. Introduction to logical programming. Search methods for problem solving: blind and informed search. Search with opponents: game analysis with minimax and alpha-beta pruning. Formalisms of knowledge representation and inference: logic, semantic networks, frames, scripts, production rules. Knowledge-based systems. Machine learning: general notions, types and paradigms of learning. Introduction to symbolic techniques of machine learning: decision trees and classification rules. Introduction to statistical machine learning techniques: naive-bayes.
For more information about the course check here.
Exploring how the artists on Spotify are related to each other with the recommendation system created within Spotify.
Classification with the dataset Gas Prices in Brazil.
To get a local copy up and running follow these simple steps.
Python 3.8 or greater, Jupyter Notebook. There are some libraries you may need to install for importing like sklearn, matplotlib and etc.
- Clone the repo
git clone https://github.com/brenoslivio/SCC0230_Artificial_Intelligence.git
- Simply run Jupyter Notebook to open the projects.
Distributed under the MIT License. See LICENSE for more information.