Predictive Analytics for Practitioners
Practical guide to predictive analytics covering data preparation, sampling, algorithm strengths/weaknesses, and model accuracy assessment. Ideal for practitioners seeking to enhance their skills in this field.
End-to-End SQL Server PowerPivot
Explore SQL Server PowerPivot add-ins for Excel and SharePoint, enabling large-scale data analysis, multidimensional modeling, and collaborative BI solutions with scheduled data refreshes and IT management.
Common Data Science Mistakes
Explore common pitfalls in data science, from data preparation to analysis. Learn to avoid mistakes in statistics, outlier handling, and visualization for more accurate insights and predictions.
Turning Membership Surveys Into Action - Predictive Analytics
Learn to transform membership survey data into actionable insights using factor analysis and predictive modeling techniques for more effective decision-making and stakeholder engagement.
Data Here, There and Everywhere - Cloud
Explore Power BI's mapping capabilities for geographical data analysis, including standard maps, ESRI options, and data visualization techniques to effectively represent location-based information.
Azure Synapse Analytics
Unified data analytics platform for ingesting, preparing, managing, and serving data, combining enterprise data warehousing and big data analytics capabilities.
Hidden Differences Between Azure ML Products Revealed
Explore Azure ML products, their differences, and use cases. Learn to create end-to-end ML workflows, integrate with SQL Server, and manage models in production using various Azure tools.
Power Query, M and Dataflow - The Lightsaber for the Data Jedi
Discover Power Query's transformation capabilities, M language benefits, and Dataflows' role in Power BI. Learn advanced features through demos to enhance your data preparation skills.
Introducing Azure Synapse Analytics - The End-to-End Analytics Platform
Explore Azure Synapse Analytics, a comprehensive platform integrating relational and big data systems for efficient data ingestion, preparation, modeling, and serving in a unified workspace.
Data Munging to Wrangling - 7 Steps to Mastering Data Preparation for Data Science
Discover essential techniques for data preparation in AI/ML projects. Learn to source, clean, and transform data effectively, enhancing the quality and predictive power of machine learning models.
Machine Learning in C# - Introduction to ML.NET
Discover ML.NET: Build machine learning applications using C# and .NET. Learn data preparation, model evaluation, and deployment techniques for integrating ML capabilities into your .NET projects.
Azure Synapse Analytics - A Data Lakehouse
Explore Azure Synapse Analytics, a unified service combining data warehousing and Big Data analytics. Learn about its features, scalability, and integration in modern data warehouses through demonstrations.
Designing Azure Data Science and AI Projects
Aprenda a diseñar proyectos de ciencia de datos e IA en Azure, desde la comprensión del negocio hasta la implementación, utilizando un enfoque práctico basado en equipo y las últimas tecnologías disponibles.
Expanding Serverless to Scale-out Kubeflow Pipelines
Discover how Nuclio ML Functions extends serverless capabilities to machine learning tasks, integrating with Kubeflow for automated scaling, experiment tracking, and streamlined ML workflows.
A Day in the Life of a Data Scientist - Conquer ML Lifecycle on Kubernetes
Explore a data scientist's daily workflow, from data prep to model deployment, using Kubeflow and Kubernetes for efficient machine learning lifecycle management.
Operating Deep Learning Pipelines Anywhere Using Kubeflow
Explore building and operating production-grade deep learning pipelines using Kubeflow, covering data preparation, storage, automation, and infrastructure management for multiple tenants.
Extending Spark Machine Learning - Beyond Linear Regression
Explore Spark's ML pipelines, learn to integrate custom tools, and understand how to build and customize advanced machine learning models for big data applications.
Forecasting the Future - An Introduction to Machine Learning for Weather Prediction in Native Ruby
Explore building weather prediction models using machine learning in Ruby, covering data preparation, linear regression, and practical implementation techniques for Rubyists of all levels.
A Developers Guide to Machine Learning
Comprehensive introduction to machine learning for developers, covering data preparation, model creation, and deployment, designed to kickstart your journey into this rapidly growing field.
A Developers Guide to Machine Learning
Comprehensive introduction to machine learning for beginners, covering data preparation, model creation, and deployment, providing a solid foundation for aspiring data scientists and developers.
What's That Fruit
Explore image classification and object detection using Microsoft Cognitive Services, from cloud-based solutions to edge computing, with simplified explanations and practical code examples.