Introduction
Use Cases
This section gives demonstrations of some business use cases built on OneNine cloud platform. This shows how easy and quick it is to drive business decisions using AI ML capabilities of the OneNine Cloud Platform.
Global Warming Time Series Forecasting
Build a Machine Learning model to predict the future temperature of the city
Efforts to understand the influence of historical climate change, at global and regional levels, have been increasing over the past decade. Specifically, air temperature forecasting has been a crucial climatic factor required for many different applications in areas such as agriculture, industry, energy, environment, tourism, etc. Some of these applications include short-term load forecasting for power utilities, air conditioning and solar energy systems development, adaptive temperature control in greenhouses, prediction and assessment of natural hazards, and prediction of cooling and energy consumption in residential buildings. Therefore, there is a need to accurately predict temperature values because, in combination with the analysis of additional features in the subject of interest, they would help to establish a planning horizon for infrastructure upgrades, insurance, energy policy, and business development.
Credit Card Fraud Detection
Build a Anamoly Detection model to recognize credit card fraud transaction
Fraud detection is a set of activities that are taken to prevent money or property from being obtained through false pretenses. It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase.
Customer Segmentation
Perform customer segmentation to understand the sales pattern and strategise the marketing
Customer segmentation is the process by which you divide your customers up based on common characteristics – such as demographics or behaviours, so you can market to those customers more effectively. These customer segmentation groups can also be used to begin discussions of building a marketing persona. This is because customer segmentation is typically used to inform a brand’s messaging, positioning and to improve how a business sells – so marketing personas need to be closely aligned to those customer segments in order to be effective.
Unversity Admission Chances
Build a Machine Learning model to predict the chances of university admission
Having an idea of the chances of admission in one's dream university is an important insight while applying. This model tells the students the areas to improve upon inorder to increase their admission chances.
Credit Risk Analysis
Perform credit risk analysis to determine credit worthiness of the applicant
Credit risk analysis is a form of analysis performed by a credit analyst on potential borrowers to determine their ability to meet debt obligations. The main goal of credit analysis is to determine the creditworthiness of potential borrowers and their ability to honor their debt obligations. If the borrower presents an acceptable level of default risk, the analyst can recommend the approval of the credit application at the agreed terms. The outcome of the credit risk analysis determines the risk rating that the borrower will be assigned and their ability to access credit.
Car CO2 Emissions Analysis
Use Machine Learning to analyze the car emissions and help reduce the impact on the environment
Insurance Sales
Predict if the customer is likely to buy the insurance policy
