This video course is built for those with a basic understanding of artificial intelligence, introducing them to advanced artificial intelligence projects as they go ahead. The first project introduces natural language processing including part-of-speech tagging and named entity extraction. Wikipedia articles are used to demonstrate the extraction of keywords, and the Enron email archive is mined for mentions and relationships of people, places, and organizations. The spaCy library is used. The next project introduces genetic algorithms. The DEAP library is used. A music data set is used in a genetic algorithm that generates a music playlist satisfying multiple criteria such as song similarity and playlist length. The last project introduces reinforcement learning and deep reinforcement learning. The OpenAI Gym platform and Q-learning algorithm are used to build a game-playing AI.
· Hands-on projects that simplify your first steps into the world of Artificial Intelligence with Python
· Master AI concepts that will get you up-and-running with AI in no time
· Leverage popular Python deep learning libraries for your Artificial Intelligence projects
1 Natural Language Processing
2 Genetic Algorithms
3 Let’s Play a Game – Reinforcement Learning
