Author: Celia
Takeaways from a Microsoft engineer about ML on Azure
Takeaways on how to run ML projects on Azure from a Microsoft engineer – author of the Azure Data Scientist Associate Certification Guide.
Andreas Botsikas – Microsoft engineer, author of the Azure Data Scientist Guide
“ML models are in fashion, such as customer churn predictions. However, it’s not easy to define what a churned customer is unless you have a multi subscription system like Netflix, where you can quickly identify the customers who stopped paying. E.g., what does churn mean for a supermarket?”
Lessons learnt with a Google engineer to leverage data for business
Leverage data and Machine Learning for business. Lessons learnt with a Google Engineer about real-world implementations.
Héctor Parra – A Google Engineer and the exciting realities of ML
“The COVID pandemic has spoiled many forecasting models. We can’t use historical data to predict a scenario that has never happened before. Many companies have not included data from 2021 to train their models because it’s biased”.
K-Means Clustering: A Simple Explanation
Post with an infographic to explain how to use K-Means Clustering from a citizen, intuitive point of view. It adds uses cases and next steps.
Data Validation and Reconciliation
Ensure data quality when copying, migrating, loading, replicating or moving data with data validation rules and reconciling records.
