Directly.me Artificial Intelligence – an Effective Guide to Understand and Learn modern AI
Do you want to learn about artificial intelligence? Do you want to design appropriate and efficient programs with artificial intelligence? Are you willing to seek help from highly qualified and experienced instructors in order to get a firm grip on artificial intelligence?

Artificial intelligence can be defined as the property of a computer or a network of neuron elements responsive to information received at its input devices nearly as responsive in the same environment information people. If the machine has a sufficient set of soft output, the machine and the person make the same movements, which generally lead to the same results in behaviour. Although the development of artificial intelligence (AI) is slowly, it is surely progressing in the technology sector. Majority of scientific developments, that significantly simplifies the lives of people, have only become possible thanks to the development of artificial intelligence.

This guide is beneficial for students – who want to know more about the basic techniques and trades behind artificial intelligence. Students should be well aware of probability theory and linear algebra in order to get full understanding of the course. This course will help you to learn:

Overview of AI (machine learning, probabilistic reasoning, robotics, and natural language processing)
Statistics, Uncertainty, and Bayes networks
Machine Learning
Logic and Planning
Markov Decision Processes and Reinforcement Learning
Hidden Markov Models and Filters
Adversarial and Advanced Planning
Image Processing and Computer Vision
Robotics and robot motion planning
Natural Language Processing and Information Retrieval
 
This efficient, convenient and effective guide has been developed and prepared by Peter Norvig (currently working as a Director of Research at Google Inc. after serving NASA as the head of the Computation Sciences Division) and Sebastian Thrun (Research Professor of Computer Science at Stanford University and a member of National Academy of Engineering and the German Academy of Sciences).
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Artificial Intelligence – an Effective Guide to Understand and Learn modern AI
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Do you want to learn about artificial intelligence? Do you want to design appropriate and efficient programs with artificial intelligence? Are you willing to seek help from highly qualified and experienced instructors in order to get a firm grip on artificial intelligence?

Artificial intelligence can be defined as the property of a computer or a network of neuron elements responsive to information received at its input devices nearly as responsive in the same environment information people. If the machine has a sufficient set of soft output, the machine and the person make the same movements, which generally lead to the same results in behaviour. Although the development of artificial intelligence (AI) is slowly, it is surely progressing in the technology sector. Majority of scientific developments, that significantly simplifies the lives of people, have only become possible thanks to the development of artificial intelligence.

This guide is beneficial for students – who want to know more about the basic techniques and trades behind artificial intelligence. Students should be well aware of probability theory and linear algebra in order to get full understanding of the course. This course will help you to learn:

Overview of AI (machine learning, probabilistic reasoning, robotics, and natural language processing)
Statistics, Uncertainty, and Bayes networks
Machine Learning
Logic and Planning
Markov Decision Processes and Reinforcement Learning
Hidden Markov Models and Filters
Adversarial and Advanced Planning
Image Processing and Computer Vision
Robotics and robot motion planning
Natural Language Processing and Information Retrieval
 
This efficient, convenient and effective guide has been developed and prepared by Peter Norvig (currently working as a Director of Research at Google Inc. after serving NASA as the head of the Computation Sciences Division) and Sebastian Thrun (Research Professor of Computer Science at Stanford University and a member of National Academy of Engineering and the German Academy of Sciences).

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