In this repository you will find a good amount of FREE resources to learn about artificial intelligence, machine learning and other related areas. Starting from basic definitions about AI to more advanced concepts. Some of these resources includes videos and free courses from trusted sources.
Feel free to add any relevant resource.
Artificial intelligence (AI) is intelligence demonstrated by machines, in contrast to the natural intelligence (NI) displayed by humans and other animals. In computer science AI research is defined as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.
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Learn more about AI: https://www.elementsofai.com/
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Other courses: https://eu.udacity.com/course/intro-to-artificial-intelligence--cs271
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(Advanced) Intro to AI http://ai.berkeley.edu/lecture_videos.html
Artificial general intelligence (AGI) is the representation of generalized human cognitive abilities in software so that, faced with an unfamiliar task, the AI system could find a solution. An AGI system could perform any task that a human is capable of.
- Learn more about AGI (SERIES OF VIDEOS) https://agi.mit.edu/
Explore some of the concepts that Computer Scientist are currently working on such as building safe Artificial General Intelligence
- AI Safety: https://youtu.be/IB1OvoCNnWY
- AI Self Improvement: https://youtu.be/5qfIgCiYlfY
- General AI Won't Want You To Fix its Code: https://youtu.be/4l7Is6vOAOA
- Concrete Problems in AI Safety : https://youtu.be/AjyM-f8rDpg
A hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds.
- What happens when our computers get smarter than we are? https://youtu.be/MnT1xgZgkpk
Machine learning is a subfield of Artificial Intelligence. In the recent years Machine Learning has been successful for the increase availability of computational processing power, data and enhancement of advanced algorithms.
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Introductory video about Machine Learning: https://youtu.be/s3MuSOl1Rog
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Neural Networks Demystified: https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&nohtml5=False
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Live example of neural network: http://playground.tensorflow.org/
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Recommended course to start learning about Machine Learning: https://github.com/PortAISociety/Learn_Machine_Learning_in_3_Months
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Other courses: https://eu.udacity.com/course/intro-to-machine-learning--ud120 , https://eu.udacity.com/course/machine-learning--ud262 , https://software.intel.com/en-us/ai-academy/students/kits/machine-learning-501 , https://ai.google/education/
Deep learning consists of multiple hidden layers in an artificial neural network. This approach tries to model the way the human brain processes light and sound into vision and hearing. Some successful applications of deep learning are computer vision and speech recognition.
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Introductory video about Deep Learning: https://youtu.be/-6INDaLcuJY?t=14m20s
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Deep into Deep Learning: http://introtodeeplearning.com/
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Reference book for Deep Learning, includes the mathematics behind Deep Learning: http://www.deeplearningbook.org/
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Recommended courses to start: https://github.com/PortAISociety/Learn_Deep_Learning_in_6_Weeks
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Other courses: https://eu.udacity.com/course/deep-learning--ud730 , http://course.fast.ai , https://software.intel.com/en-us/ai-academy/students/kits/deep-learning-501
Reinforcement learning (RL) is an area of machine learning concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward.
- Deepmind video lecture on Advanced Deep Learning and Reinforcement Learning: https://www.youtube.com/playlist?list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs
- OpenAI introduction to Reinforcement Learning looking at the algorithms: https://spinningup.openai.com/en/latest/
- Extensive portfolio of free resources to learn Reinforcement Learning, from basics to advanced concepts: https://gameplaying.ai/