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What is reinforcement learning?

What is reinforcement learning?

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

Federated Learning

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) Technology

Natural Language Processing (NLP) Technology

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.

ML | Geometric Deep Learning

ML | Geometric Deep Learning

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.

Integrated AI & Analytics

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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