On Demand Workshop
Scaling Machine Learning Workflows with Apache Spark
Master Distributed Machine Learning at Your Pace: On-Demand Apache Spark Workshop
Gain valuable insights into distributed machine learning with our on-demand workshop, Scaling Machine Learning Workflows with Apache Spark. This session is tailored for those eager to understand the fundamentals of scaling ML models using Apache Spark—no prior experience required. Enjoy flexible, self-paced learning while building practical skills through hands-on demonstrations and expert guidance.
Date
On-Demand
Location
Online
Language
English
Speakers
1
Key Topics Covered
Understanding Distributed Machine Learning Paradigms
Techniques for scaling ML workflows with Apache Spark
Practical Considerations and Best Practices
Who Should Watch Distributed ML Workshop:
This session is designed for:
- Beginners interested in distributed machine learning techniques
- Professionals seeking to scale their machine learning workflows using Apache Spark
- Data scientists and engineers looking for practical solutions to real-world ML scaling challenges
About the trainer
Nitin Bhushan
Nitin Bhushan, a seasoned data scientist with extensive experience in AI, data science, and engineering projects, leads this workshop. With a strong background in developing applied AI programs and a passion for data-driven innovation, Nitin offers practical insights to help you succeed.
Check our Machine Learning Courses
Create data visualizations in Python using several different libraries.
Build a solid foundation of data warehousing and modeling with this training. You’ll learn everything about data warehouse architectures, formal data modeling, performance tuning and more.
Register now
Don’t miss this opportunity to enhance your skills in distributed machine learning and learn how to effectively scale your ML workflows with Apache Spark.
Feel free to contact us. We’re happy to help!
