Artificial Intelligence & Machine Learning Application

Our company advertises thousands of products, and we want to leverage the latest technology to gain market advantage. Applications of this technology include recommendation algorithms, predictive analytics like lifetime values, fraud detections, and classifications.We would like to collaborate with students to apply the latest artificial intelligence (AI) and machine learning (ML) techniques to our existing dataset. Students will develop an AI / ML model related to any of the aforementioned applications.This will involve several different steps for the students, including:Conducting background research on our existing products and the dataset.Analyzing our current dataset.Researching the latest AI / ML techniques and how they could be applied to our data.Developing an AI / ML model that provides unique outcomes or insights into our data.Providing multiple solutions that can be applied to solve the same problem.

Analyzing Industry Data

Our company advertises thousands of products online. We believe we know a lot about our consumers and target consumer base, but we need to look beyond the buyer and examine our industry.We would like to collaborate with students to identify key market trends and assist in our go-forward plans.This will involve several different steps for the students, including:Familiarizing themselves with our products, target market, and industry.Analyzing growth trends, stagnation patterns and decline analytics.Identifying areas of promising innovation and areas that are slowing down.Bonus steps in the process would also include:Recommending strategies to best position our company.

Financial Risk Analysis

As a growing company, we are interested in understanding the state of the market we are in, and our organization’s level of risk. In this project, students will assess our company’s risk by building a financial risk model to determine our best course of action. Students will perform a sensitivity analysis to help us eliminate some of the uncertainties we face and determine the reliability of risk estimates. This may involve:Using mathematical and statistical tools to analyze private and public data.Evaluating metrics associated with the risk level of our company such as volatility, correlations for returns, forward/futures contracts, cash flows, variance, and economic states.Building a financial risk model including sensitivity analysis to determine the reliability of the model’s findings.Creating a report to present the results and recommendations from various forms of analysis to be presented to the project manager.