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Mastering Automated Machine Learning Models Implementation

Mastering Automated Machine Learning Models Implementation

$199.00
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Includes a practical, ready-to-use toolkit with implementation templates, worksheets, checklists, and decision-support materials so you can apply what you learn immediately - no additional setup required.
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Mastering Automated Machine Learning Models Implementation



Course Curriculum

This comprehensive course is designed to equip participants with the skills and knowledge required to implement automated machine learning models. Upon completion, participants will receive a certificate issued by The Art of Service.

Course Overview

The course is divided into 8 chapters, covering over 80 topics, and is designed to be interactive, engaging, and comprehensive. Participants will learn through a combination of video lessons, hands-on projects, and real-world applications.

Chapter 1: Introduction to Automated Machine Learning

  • Overview of Automated Machine Learning (AutoML)
  • Benefits and limitations of AutoML
  • Applications of AutoML in real-world scenarios
  • Introduction to popular AutoML tools and frameworks

Chapter 2: Machine Learning Fundamentals

  • Supervised, unsupervised, and reinforcement learning
  • Regression, classification, clustering, and dimensionality reduction
  • Model evaluation metrics and techniques
  • Overfitting, underfitting, and regularization techniques

Chapter 3: Data Preprocessing for AutoML

  • Importance of data preprocessing in AutoML
  • Handling missing values and outliers
  • Data normalization and feature scaling
  • Feature engineering and selection techniques

Chapter 4: AutoML Tools and Frameworks

  • In-depth exploration of popular AutoML tools and frameworks, including:
    • H2O AutoML
    • Google AutoML
    • Microsoft Azure Machine Learning
    • Amazon SageMaker Autopilot
  • Comparison of features and capabilities
  • Practical exercises using different AutoML tools and frameworks

Chapter 5: Implementing AutoML Models

  • Step-by-step guide to implementing AutoML models using various tools and frameworks
  • Hyperparameter tuning and model optimization techniques
  • Model interpretability and explainability techniques
  • Model deployment and serving strategies

Chapter 6: Advanced AutoML Topics

  • Transfer learning and few-shot learning
  • Ensemble methods and stacking
  • Handling imbalanced datasets and class weighting
  • Using AutoML with other AI and ML techniques

Chapter 7: Real-World Applications of AutoML

  • Case studies of AutoML in various industries, including:
    • Healthcare
    • Finance
    • Marketing
    • Customer service
  • Practical exercises and group discussions

Chapter 8: Final Project and Certification

  • Participants will work on a final project to implement an AutoML model using a real-world dataset
  • Guidance and feedback from expert instructors
  • Upon completion, participants will receive a certificate issued by The Art of Service

Course Features

  • Interactive and engaging video lessons and hands-on projects
  • Comprehensive coverage of AutoML topics and tools
  • Personalized feedback and guidance from expert instructors
  • Up-to-date content and real-world applications
  • Practical exercises and projects to reinforce learning
  • Flexible learning schedule and lifetime access to course materials
  • User-friendly and mobile-accessible course platform
  • Community-driven discussion forums and support
  • Actionable insights and takeaways
  • Gamification and progress tracking to enhance learning experience
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