Data Science Solutions with Cortana Analytics

Explore how to build and operationalize data science solutions using Cortana Analytics in this comprehensive tutorial from ODSC West 2015. Learn to create end-to-end predictive models using Microsoft Azure Machine Learning studio, leveraging its extensive library of machine learning algorithms and R and Python language extensibility. Walk through typical machine learning steps including data ingestion, cleaning, exploration, feature engineering, model selection, and result evaluation. Gain hands-on experience fine-tuning models and deploying experiments as web services. Discover the Cortana Analytics Suite, work with the Scaleup Repository, and practice exercises in Azure ML Studio. Led by experienced data scientists Fidan Boylu and Muxi Li, this session provides valuable insights into building and implementing advanced analytics solutions across various domains such as predictive maintenance and fraud detection.

Introduction
Cortana Analytics Suite
Scaleup Repository
Studio
Exercises
Workspace
Upload Data
Exclude Columns
Evaluate Module
Deploy Web Service
Add Metadata
Create Model
Evaluate Model
Demo