Learn How to Leverage Python modules for Advanced Analytics, How to Codify ML Algorithms for Descriptive Analytics, and How to deploy Python/Jupyter Notebook with Analytics Solutions

Date and Time:
17^th Dec. 2020 – 4 PM CET | 9 AM CST

Implementing Manufacturing Data Analytics solution need a layered and guided approach to realize ‘Return on Analytics’ (ROA) before investing big dollars. This analytics e-meet is focused how to approach advanced analytics by using Python/Jupyter notebook, methods and best practices to work on process (time-series) data and advanced visualization. The session will showcase prevalent prerequisites and use cases such as statistical inference on process variability, correlation /deterministic analysis, significance testing and model building, etc. The data science / analyst team would get the insights into Advanced Data Analytics templatization.

Meet our experts and get insights into:

• Approach: Process Data Mapping and Representation – Prerequisites

• Methods: How to templatizeRoot Cause Analysis, Predictive Analytics, Performance Analysis, Model Building and Fingerprint of a Process, Visual Analytics 

• Solutions: Advanced Visualization, Deployment of Python model, Integration with Analytic Solutions