This is the Windows app named AI Platform Training and Prediction whose latest release can be downloaded as cloudml-samplessourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named AI Platform Training and Prediction with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.
- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application and install it.
- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.
Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.
SCREENSHOTS
Ad
AI Platform Training and Prediction
DESCRIPTION
AI Platform Training and Prediction is a collection of machine learning example projects that demonstrate how to train, deploy, and serve models using Google Cloud AI Platform and related services. It includes a wide variety of implementations across frameworks such as TensorFlow, PyTorch, scikit-learn, and XGBoost, allowing developers to explore different approaches to building ML solutions. The repository covers the full machine learning lifecycle, including data preprocessing, model training, hyperparameter tuning, evaluation, and prediction serving. It also demonstrates how to scale from local training to distributed cloud-based training without major code changes, making it a valuable resource for transitioning workloads to production environments. Although the repository has been archived, it still provides extensive reference implementations and practical examples for learning cloud-based ML workflows.
Features
- Sample projects for training and deploying ML models
- Support for multiple frameworks like TensorFlow and PyTorch
- End-to-end workflows from data processing to prediction
- Examples for distributed and scalable training
- Jupyter notebooks for interactive experimentation
- Real-world datasets and use case demonstrations
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/ai-platform-train-pred.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
