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I want to plug an AI engine directly into my Windows-based proprietary program so it can make sense of the data we already collect—primarily log/transcript text and sensor-generated numbers. At the moment the application stores everything locally; what is missing is a bridge that feeds this information to a model built in TensorFlow or PyTorch and then returns the predictions, classifications, or anomaly scores back into the software in real time (or near real time). Here is the outcome I’m aiming for: • A clean interface layer—DLL, API service, or direct Python-C# binding—that my program can call with raw records and receive structured results. • A working model (or framework for training one) capable of handling combined text + numerical inputs; think language models for the logs and a lightweight neural net or classical pipeline for the sensor metrics, merged as needed and presented into a report format. • Clear instructions and sample code showing how to retrain or update the model as new data arrives. • Minimal disruption to the existing UI; insights will flow into a new app or platform and present innate data in useful information. If you have experience embedding TensorFlow/PyTorch solutions into Windows desktop environments and can keep everything self-contained behind our firewall, I would love to hear how you would approach it and how long you expect the hand-off to take.
Mã dự án: 40337316
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skaneateles, United States
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Thành viên từ thg 8 28, 2013
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