🤣
Seriously though two things have cut through:
- “it’s better to under-promise and over-deliver”
- “maybe it will work, but we absolutely have to do a validation study first”
spherical_projection
joined 1 year ago
We are small company so I do a huge range of stuff.
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New product dev from data collection through to model in production.
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Improving our internal annotation tools
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Automating workflows and pipelines.
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Database wrangling, APIs and UI
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Managing the other ML engineers
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Business development
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Stop CEO promising clients that AI can solve everything.
Tools:
IDE: JetBrains suite / VS 2022 / VS Code Languages: C# and Python Frameworks: .NET 7, PyTorch, ONNX. Backend: ASP.NET Core for the heavy stuff or production, else Flask Front end : Blazor WASM and occasionally Blazor server. Deployment: Local server or Azure cloud. Collaboration: Microsoft Teams and Microsoft Loop
No, I finally changed from Tensorflow Keras to PyTorch and not going back.
Why abandon keras? In the end I felt like I was always fighting some little bug or error that needed brute force guessing to resolve. The data loaders are painful. Dealing with idiosyncrasies of the model subclass system to do anything custom.