Hands-on Artificial Intelligence with TensorFlow, published by Packt
This is the code repository for Hands-on Artificial Intelligence with TensorFlow [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
TensorFlow is one of the most commonly used frameworks for Deep Learning and AI. This course will be your guide to understand and learn the concepts of Artificial intelligence by applying them in a real-world project with TensorFlow. This course will show you how to combine the power of Artificial Intelligence and TensorFlow to develop some exciting applications for the real world. This course will take you through all the relevant AI domains, tools, and algorithms required to build optimal solutions and will show you how to implement them hands-on. You will then be taken through techniques such as reinforcement learning, heuristic searches, neural networks, Computer Vision, OpenAI Gym, and more in different stages of your application. This course will show you how to implement AI practically using TensorFlow models and how it eases the way you interact with the technology. You will learn how TensorFlow can be used to analyze a variety of data sets and will learn to optimize various AI algorithms. By the end of the course, you will have learned to build intelligent apps by leveraging the full potential of Artificial Intelligence with TensorFlow.
- Explore the current state of Machine Learning and Artificial Intelligence.
- Develop the understanding to build AI systems using different machine learning models
- Optimize machine learning models for better performance and accuracy
- Understand different deep learning models for computer vision
- Explore generative models and how they generate information from random noise
- Code the most trending AI algorithms that outperform humans in video games
To fully benefit from the coverage included in this course, you will need:
This course is for Developers and aspiring Data Science professionals who would like to develop their AI techniques to create smart and robust applications. Basic ML concepts and basic Tensorflow knowledge would be required for this course.
This course has the following software requirements:
TensorFlow
Jupyter Notebook
