Filtering by
- All Subjects: artificial intelligence
- Creators: Arts, Media and Engineering Sch T
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Song Sift is an application built using Angular that allows users to filter and sort their song library to create specific playlists using the Spotify Web API. Utilizing the audio feature data that Spotify attaches to every song in their library, users can filter their downloaded Spotify songs based on four main attributes: (1) energy (how energetic a song sounds), (2) danceability (how danceable a song is), (3) valence (how happy a song sounds), and (4) loudness (average volume of a song). Once the user has created a playlist that fits their desired genre, he/she can easily export it to their Spotify account with the click of a button.
This project explores the potential of an artificial intelligence/machine learning algorithm, K-Means to augment the connection between two individuals through a game interface. Further implementation of such technology is theorized in the form of a two-way chatbot. The role of bias is extensively reported and researched in order to remain cognizant of these new technological advancements.
This project explores the potential of an artificial intelligence/machine learning algorithm, K-Means to augment the connection between two individuals through a game interface. Further implementation of such technology is theorized in the form of a two-way chatbot. The role of bias is extensively reported and researched in order to remain cognizant of these new technological advancements.
This project explores the potential of an artificial intelligence/machine learning algorithm, K-Means to augment the connection between two individuals through a game interface. Further implementation of such technology is theorized in the form of a two-way chatbot. The role of bias is extensively reported and researched in order to remain cognizant of these new technological advancements.
This project explores the potential of an artificial intelligence/machine learning algorithm, K-Means to augment the connection between two individuals through a game interface. Further implementation of such technology is theorized in the form of a two-way chatbot. The role of bias is extensively reported and researched in order to remain cognizant of these new technological advancements.
This project explores the potential of an artificial intelligence/machine learning algorithm, K-Means to augment the connection between two individuals through a game interface. Further implementation of such technology is theorized in the form of a two-way chatbot. The role of bias is extensively reported and researched in order to remain cognizant of these new technological advancements.
This project explores the potential of an artificial intelligence/machine learning algorithm, K-Means to augment the connection between two individuals through a game interface. Further implementation of such technology is theorized in the form of a two-way chatbot. The role of bias is extensively reported and researched in order to remain cognizant of these new technological advancements.
For my Honors Thesis, I decided to create an Artificial Intelligence Project to predict Fantasy NFL Football Points of players and team's defense. I created a Tensorflow Keras AI Regression model and created a Flask API that holds the AI model, and a Django Try-It Page for the user to use the model. These services are hosted on ASU's AWS service. In my Flask API, it actively gathers data from Pro-Football-Reference, then calculates the fantasy points. Let’s say the current year is 2022, then the model analyzes each player and trains on all data from available from 2000 to 2020 data, tests the data on 2021 data, and predicts for 2022 year. The Django Website asks the user to input the current year, then the user clicks the submit button runs the AI model, and the process explained earlier. Next, the user enters the player's name for the point prediction and the website predicts the last 5 rows with 4 being the previous fantasy points and the 5th row being the prediction.