Technical

Practical Machine Learning

Hands-on training for implementing and maintaining machine learning models that solve real business problems.

Duration

3 days

Level

Intermediate

Audience

Data Scientists, Developers

This hands-on workshop bridges the gap between theoretical machine learning knowledge and practical implementation. Participants will work through complete ML projects from problem formulation to deployment and monitoring.

You'll learn how to build ML solutions that address real business problems, handle messy real-world data, and create systems that can be reliably deployed and maintained in production.

Prerequisites

  • Basic Python programming skills
  • Familiarity with data analysis concepts
  • Understanding of basic statistics
  • Experience with pandas and numpy is helpful but not required

Who Should Attend

  • Data scientists moving from theory to practice
  • Software developers expanding into ML implementation
  • Analytics professionals upgrading their toolkit
  • ML engineers looking to improve their end-to-end skills

What You'll Learn

Develop end-to-end ML solutions following industry best practices
Learn effective feature engineering for real-world datasets
Master model evaluation, validation, and interpretation techniques
Implement ML pipelines that integrate with production systems
Apply practical debugging and improvement strategies for ML models

Ready to Join?

Register for this workshop or request more information.

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Ready to Transform Your Business?

Let's discuss how my AI and software solutions can help you achieve your goals.