Thinxtream can rapidly enable
your Connected Products and Smart Services business
Build IoT intelligence with our in-depth expertise in Azure Machine Learning
AZURE MACHINE LEARNING
Thinxtream has had a long partnership with Microsoft® and uses Azure® Machine Learning, Microsoft’s integrated, end-to-end data science and advanced analytics solution, with extensive support for industry standard open-source libraries and toolkits to develop intelligent IoT solutions.
- Support for data ingestion from various Azure/Non-Azure data storage services
- Advanced data preparation techniques like Filtering, Normalization, Principal Component Analysis, Partitioning and Sampling, etc.
- Extend Azure Machine Learning model with R and Python™ Script modules
- Making predictions with Elastic APIs like Request Response and Batch Execution Service
- Model Visualizations with Scatterplots, Bar Charts, Box plots, Histograms, REPL with Jupyter™ Notebook
- Retraining model, Cross validation and Parameter Sweeping
- Support for wide range of data formats - ARFF, CSV, SVMLight, TSV, Excel®, ZIP
- Integrating open source technologies like Scikit-learn, TensorFlow™, Microsoft Cognitive Toolkit (CNTK), Spark ML
- Industry standard regression algorithms for training models, including Linear Regression, Deep Neural Networks, Decision Forest, Fast Forest Quantile, Ordinal Regression and Poisson Regression
- Manage entire data science life cycle with cross-platform Desktop application - Azure Machine Learning Workbench
- Deploy Azure Machine Learning models into wide variety of environments like local/on-prem devices, Docker images, IoT Edge devices, Azure Container Services (ACS)