The Data Science Toolkit provides Data Scientists, Solution Architects and delivery teams, with packaged, vetted and tested delivery accelerators,
delivery guidance and product backlogs for common machine learning scenarios.
You can use the delivery accelerators, delivery guides and product backlogs listed below in your delivery engagements.
You can also contribute new material or update existing material or simply browse through the content. Please don't forget to reach out with any comments or contributions.
Estimate future sales values
Uses computer vision for object or defect detection and includes edge deployment capabilities.
ML Ops support for Databricks
Configurable CI/CD pipelines, AML pipelines, and compute resources for ML Ops.
ML Ops for 1000's of similar ML Models
Knowledge mining on unstructured data sets with no data labeling.
Fuzzy Matching People to projects and Data Management examples like deduplication, entity matching
Pre-configured engine for demand forecasting, map data into the existing model to generate a forecast.
Create clusters of customers based on recency, frequency and value.
Predict the total business worth of a customer over the lifetime of the relationship
Calculate retention rates by customer segment and product
Collection of modules to help with validation, identification and authentication processes
Binary classification, with parameter based auto algorithm selection.
Detect anomalies on very large structured data sets
GLUE is a lightweight, Python-based collection of scripts to support you at succeeding with speech and text us