Machine Learning for Azure Databricks Course Overview
Explore the 'Machine Learning for Azure Databricks Course Overview' by Microsoft, designed for data scientists, engineers, and analysts. This course is essential for mastering machine learning techniques in a cloud environment, enabling professionals to harness the power of big data and advanced analytics, fostering innovation and improving data-driven decision-making across industries.
Course outline & what you'll learn
Overview of Azure Databricks
- Importance of Machine Learning in Databricks
- Creating an Azure Databricks workspace
- Configuring clusters for machine learning
- Data ingestion techniques
- Exploratory data analysis with Spark
- Introduction to machine learning concepts
- Supervised vs. unsupervised learning
- Feature engineering and selection
Overview of MLlib library
- Implementing algorithms for classification and regression
- Metrics for model evaluation
- Hyperparameter tuning techniques
- Model serving in Azure Databricks
- Integration with Azure Machine Learning
- Performance tuning in Azure Databricks
- Best practices for machine learning workflows
- Industry use cases for machine learning in Databricks
- Analyzing success stories and lessons learned
- Review of key concepts
- Resources for further learning and exploration
Why train with Traincrest
This Microsoft course is delivered by Traincrest's certified instructors, live online or in the classroom, with hands-on labs and a 98% exam success rate. Trusted by 500+ companies and 50,000+ students worldwide.