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  01. Introduction

   001. Why you need to know about artificial intelligence.mp4

  02. What Is Artificial Intelligence

   002. Define general intelligence.mp4

   003. The general problem-solver.mp4

   004. Strong vs. weak AI.mp4

  03. The Rise of Machine Learning

   005. Machine learning.mp4

   006. Artificial neural networks.mp4

  04. Common AI Systems

   007. Searching for patterns in data.mp4

   008. Robotics.mp4

   009. Natural language processing.mp4

   010. The Internet of Things.mp4

  05. Learn from Data

   011. Labeled and unlabeled data.mp4

   012. Massive datasets.mp4

  06. Identify Patterns

   013. Classify data.mp4

   014. Cluster data.mp4

   015. Reinforcement learning.mp4

  07. Machine Learning Algorithms

   016. Common algorithms.mp4

   017. K-nearest neighbor.mp4

   018. K-means clustering.mp4

   019. Regression.mp4

   020. Naive Bayes.mp4

  08. Fit the Algorithm

   021. Select the best algorithm.mp4

   022. Follow the data.mp4

   023. Overfitting and underfitting.mp4

  09. Artificial Neural Networks

   024. Build a neural network.mp4

   025. Weighing the connections.mp4

   026. The activation bias.mp4

  10. Improve Accuracy

   027. Learning from mistakes.mp4

   028. Step through the network.mp4

  11. Where to Go from Here

   029. Using AI systems.mp4

   030. Applying AI to solve problems.mp4

  Bonus Resources.txt