Advanced Artificial Intelligence Projects with Python

Description

Considered the Holy Grail of automation, data analysis, and robotics, Artificial Intelligence has taken the world by storm as a major field of research and development. Python has surfaced as a dominate language in AI/ML programming because of its simplicity and flexibility, in addition to its great support for open source libraries such as spaCy and TensorFlow. 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. The code bundle for this video course is available at - https://github.com/PacktPublishing/Advanced-Artificial-Intelligence-Projects-with-Python. Style and Approach: Built for AI enthusiasts, machine learning and deep learning students, and developers across three realistic projects, this course covers modern techniques that will take your AI game with Python to the next level. 

Business Outcomes  

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

Learning Outcomes

• Extract names, places, and more and their relationships from text


• Build a recommendation engine for finding new music


• Use deep reinforcement learning to build an AI that plays arcade games


• Employ the SpaCy and textacy libraries for natural language processing


• Use popular libraries such as Keras and TensorFlow for reinforcement learning 

Who Should Attend

Are you a Python programmer with a basic understanding of machine learning and minimal experience in developing AI projects? This is the video course that you need to take your game to the next level. Build advanced AI applications using powerful and popular Python deep learning libraries that help you interact intelligently with the world around you. 

Frequently Asked Questions