Artificial Intelligence Foundations: Machine Learning

Contents

• Introduction Introduction

  • Introduction to AI foundations: Machine learning course

    46s
  • Reviewing the course scenarios

    2m 39s
• 1. Understanding Machine Learning 1. Understanding Machine Learning

  • Exploring machine learning

    3m 11s
  • Examining how machines learn

    3m 36s
• 2. Implementing a Machine Learning Solution 2. Implementing a Machine Learning Solution

  • Breaking down the machine learning lifecycle

    3m 46s
  • Framing machine learning problems

    4m 10s
  • Identifying a pre-built model

    3m 52s
  • Understanding tools used to train a model

    4m 18s
• 3. Preparing Data for Machine Learning 3. Preparing Data for Machine Learning

  • Obtaining data

    4m 37s
  • Visualizing and understanding data

    4m 51s
  • Understanding feature engineering

    4m 56s
  • Demo: Performing feature engineering

    5m 58s
• 4. Training a Machine Learning Model 4. Training a Machine Learning Model

  • Understanding learning algorithms and model training

    4m 8s
  • Exploring learning algorithms for classification

    4m 27s
  • Reviewing learning algorithms for regression

    5m 23s
  • Examining additional learning algorithms

    4m 25s
  • Training a custom machine learning model

    5m 2s
  • Demo: Training a custom machine learning model

    7m 39s
• 5. Evaluating Model Performance 5. Evaluating Model Performance

  • Exploring common classification metrics

    4m 49s
  • Understanding the confusion matrix

    4m 4s
  • Exploring common regression metrics

    5m 14s
  • Determining feature importance

    4m 25s
  • Combating bias

    3m 38s
• 6. Operationalizing a Machine Learning Pipeline 6. Operationalizing a Machine Learning Pipeline

  • Structuring a machine learning pipeline

    3m 59s
  • Demo: Designing and building a pipeline

    5m 4s
• Conclusion Conclusion

  • Your machine learning journey

    1m 59s