The client began experiencing an increase in the volume of spam through its estimate request form. Utilizing old data, we determined we could go through the clients request history and flag the spam, then use machine learning to train a simple model to classify estimate requests as spam or not spam.
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Automated Predictive Analytics is an advanced form of data analytics that uses machine learning algorithms to analyze large amounts of data and make predictions about future events. This technology can be used to identify trends, forecast outcomes, and make decisions about how to best proceed in a given situation.
Reinforcement learning (RL) is an area of machine learning that focuses on how an agent takes actions within an environment in order to maximize a reward. This type of learning involves trial and error, with the agent receiving positive reinforcement when it performs a desired behavior, and negative reinforcement when it doesn’t. In this way, the agent is able to learn from its mistakes and adjust its behavior accordingly.
Federated learning is a type of machine learning where data is distributed among different devices, instead of being centralized in a single server. Devices can be trained locally on their own data, and then share their model updates with each other, without sharing the underlying data.
Natural language processing (NLP) is a subfield of linguistics, computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.
Geometric deep learning is a type of machine learning that is based on geometric data, such as images, 3D models, and point clouds. It is a relatively new field that is growing rapidly due to the increasing amount of data that is available in these formats.
In the insurance industry, machine learning is being used in the insurance industry to automate underwriting and rating processes. This is making these processes more efficient and accurate, providing benefits which include reduced costs, improved accuracy, and faster turnaround times.
Integrate AI & Analytics by leveraging the Microsoft ML.NET platform we are able to quickly and efficiently build and train data models so that you can ask the questions.
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