- Convert Business problem to a Data Science problem.
- Start with a reasonable objective.
- Identify the right technologies, architectures, and models for the problem.
- Add human intelligence and domain knowledge to build robust features.
- Build a scalable and end-to-end training and inferencing pipeline.
- Launch and iterate while adding new features to the pipeline.
Machine learning algorithms
Are modeled in many ways on human minds
Cloud ML Infrastructure Services
Our areas of expertise
- Descriptive and Predictive analysis of structured data.
- Computer vision – Object detection based signature detection in scanned documents. Image-based document classification and extraction
- NLP – Named entity recognition, Sequence to Sequence modeling, Sentiment analysis, Text-based classification.
Uber Auto-Rickshaw App
Farmer engagement and commerce platform