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Source channel @githubtrending · Post #15121 · Sep 5

#jupyter_notebook#chatgpt#finance#fingpt#fintech#large_language_models#machine_learning#nlp#prompt_engineering#pytorch#reinforcement_learning#robo_advisor#sentiment_analysis#technical_analysis FinGPT is an open-source AI tool designed specifically for finance, helping you analyze financial news, predict stock prices, and get personalized investment advice quickly and affordably. Unlike costly models like BloombergGPT, FinGPT can be updated frequently with new data at a low cost, making it more accessible and timely. It uses advanced techniques like reinforcement learning from human feedback to tailor advice to your preferences, such as risk tolerance. You can use FinGPT for tasks like sentiment analysis, robo-advising, fraud detection, and portfolio optimization, helping you make smarter financial decisions with up-to-date insights. https://github.com/AI4Finance-Foundation/FinGPT

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@githubtrending · Post #14691 · 05/10/2025, 12:00 AM

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#csharp#architecture#aspnetcore#clean_architecture#cqrs#ddd#dotnet#dotnetcore#event_driven_architecture#event_sourcing#kubernetes#masstransit#messaging#microservice#microservices#oauth2#opentelemetry#software_architecture#software_design#software_engineering#vertical_slice_architecture Migrating from a monolithic architecture to a cloud-native microservices architecture offers several benefits. It improves scalability, allowing different parts of the application to grow independently. This approach also enhances reliability by isolating faults, so if one service fails, others continue to work. Additionally, microservices enable faster deployment and updates, as each service can be developed and deployed separately. This flexibility allows teams to use the best technology for each service, making development more efficient and agile[2][3][5]. https://github.com/meysamhadeli/monolith-to-cloud-architecture