Why you need to know about artificial intelligence

Contents

• Introduction Introduction

  • Why you need to know about artificial intelligence

    49s
• 1. What Is Artificial Intelligence? 1. What Is Artificial Intelligence?

  • Define general intelligence

    3m 13s
  • The general problem-solver

    3m 7s
  • Strong vs. weak AI

    3m 1s
• 2. The Rise of Machine Learning 2. The Rise of Machine Learning

  • Machine learning

    3m 20s
  • Artificial neural networks

    3m 5s
• 3. Common AI Systems 3. Common AI Systems

  • Searching for patterns in data

    3m 35s
  • Robotics

    3m 19s
  • Natural language processing

    3m 26s
  • The Internet of Things

    3m 18s
• 4. Learn from Data 4. Learn from Data

  • Labeled and unlabeled data

    3m 7s
  • Massive datasets

    3m 40s
• 5. Identify Patterns 5. Identify Patterns

  • Classify data

    3m 22s
  • Cluster data

    3m 24s
  • Reinforcement learning

    3m 9s
• 6. Machine Learning Algorithms 6. Machine Learning Algorithms

  • Common algorithms

    3m 19s
  • K-nearest neighbor

    3m 19s
  • K-means clustering

    3m 31s
  • Regression

    3m 25s
  • Naive Bayes

    3m 29s
• 7. Fit the Algorithm 7. Fit the Algorithm

  • Select the best algorithm

    3m 21s
  • Follow the data

    3m 1s
  • Overfitting and underfitting

    3m 19s
• 8. Artificial Neural Networks 8. Artificial Neural Networks

  • Build a neural network

    3m 22s
  • Weighing the connections

    3m 3s
  • The activation bias

    3m 2s
• 9. Improve Accuracy 9. Improve Accuracy

  • Learning from mistakes

    3m 23s
  • Step through the network

    3m 46s
• 10. Where to Go from Here 10. Where to Go from Here

  • Using AI systems

    3m 14s
  • Applying AI to solve problems

    1m 22s