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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Machine Learning, or ML, is an increasingly popular technology in the world of finance. It is a branch of artificial intelligence (AI) that uses algorithms and statistical models to allow computers to learn from data and make decisions with minimal human intervention. ML is being used in the financial sector for a variety of tasks, from predicting stock prices and trading strategies to fraud detection and customer segmentation.
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.
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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