Optimizing Machine Learning Performance

This course is part of Machine Learning: Algorithms in the Real World Specialization

Instructor: Anna Koop

Skills you'll gain

  •   Data Maintenance
  •   Data Ethics
  •   Ethical Standards And Conduct
  •   Machine Learning
  •   Business Strategy
  •   Applied Machine Learning
  •   Performance Metric
  •   Production Planning
  •   Business Operations
  •   Risk Mitigation
  •   MLOps (Machine Learning Operations)
  •   Systems Integration
  •   Maintainability
  •   Stakeholder Communications
  •   Operational Analysis

    • There are 4 modules in this course

    To be successful, you should have at least beginner-level background in Python programming (e.g., be able to read and code trace existing code, be comfortable with conditionals, loops, variables, lists, dictionaries and arrays). You should have a basic understanding of linear algebra (vector notation) and statistics (probability distributions and mean/median/mode). This is the final course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute (Amii).

    Responsible Machine Learning

    Machine Learning in Production & Planning

    Care and Feeding of your Machine Learning System

    Explore more from Machine Learning

    Machine Learning Algorithms: Supervised Learning Tip to Tail

    Developing Machine Learning Solutions

    Data for Machine Learning

    Machine Learning Algorithms

    ©2025  ementorhub.com. All rights reserved