This was achieved by first using offline explorer, an application that can download websites, to gather job postings from Dice.com that were searched by a pre-defined list of technical skills. Next came the parsing of the downloaded postings to extract and clean the data that was required and filling a database with that cleaned data. Then the companies were matched up with their corresponding industries. This was done using their NAICS (North American Industry Classification System) codes. The descriptions were then analyzed, and a group of soft skills was chosen based on the results of Word2Vec (a group of models that assists in creating word embeddings). A master table was then created by combining all of the tables in the database. The master table was then filtered down to exclude posts that required too much experience. Lastly, the web app was created using node.js as the back-end. This web app allows the user to choose their desired criteria and navigate through the postings that meet their criteria.
This project examines the effectiveness and key performance indicators of state prisons across the country in order to establish how Arizona’s prisons compare. Variables such as the daily inmate cost, annual budget, and the percentage of the budget spent on healthcare are all examined for a measurable impact on recidivism rate, which is the rate at which individuals released from prison re-offend and return to prison. The findings and next steps for the correctional industry are slightly controversial but will prove effective in improving the industry.
The purpose of this paper is to discuss the history of artificial intelligence (AI) and its future implications in the healthcare industry. Utilizing information from research and medical journals, this paper will examine the foundations of AI and the people and events that influenced its development. Further, the various subsets of AI and its use in contemporary life will be discussed. While the technological evolution of AI will be discussed, this paper is not a technical treatise on the inner workings of AI software and technology, rather, it is a basic history of the development of AI and its respective subsets, and a look at current and potential future applications of AI. This information will be applied to the healthcare industry to discuss the history of AI in this field, detailing how AI was developed to find innovative solutions to complex medical problems. Finally, future prospects of AI in the medical industry will be discussed, explaining potential applications of this technology as well as various challenges and implications.