TUM Course - "Artificial Intelligence in Automotive Technology" - Lecture 10

TUM Course - "Artificial Intelligence in Automotive Technology" - Lecture 10 Topic: Recurrent Neuronal Networks Lecturer: Christian Dengler Welcome to the TUM course "Artificial Intelligence in Automotive Technology". In 13 different lectures we will teach you the foundations of Artificial Intelligence with regard to its use in automotive technology. After each lecture will have and additional practice session where we provide coding examples for the discussed methods. Beside these videos you can find the course material (.pdf and .pptx) we made for this lecture on the homepage of the Institute of Automotive Technology from the Technical University of Munich: https://www.ftm.mw.tum.de/index.php?id=1613&L=1 The additional coding material for the practice session in each lecture can be found on our Github Repository: https://github.com/TUMFTM/Lecture_AI_in_Automotive_Technology Lecture Overview: Lecture 1 - Introduction: Artificial Intelligence: https://youtu.be/f_VvScVwBGU Lecture 2 - Computer Vision: https://youtu.be/9fTCZ1QPLIg Lecture 3 - Supervised Learning: Regression: https://youtu.be/kgOessQts_Q Lecture 4 - Supervised Learning: Classification: https://youtu.be/Ow_q7htvo-8 Lecture 5 - Unsupervised Learning: Clustering: https://youtu.be/eVpsqvdZrTE Lecture 6 - Path Finding: From British Museum to A* : https://youtu.be/d5lyM2or8cs Lecture 7 - Introduction Neuronal Networks: https://youtu.be/ksxzoG5YktY Lecture 8 - Deep Neural Networks: https://youtu.be/T3kQLnWpeCg Lecture 9 - Convolutional Neuronal Networks: https://youtu.be/3YccAgMwgRM Lecture 10 - Recurrent Neuronal Networks: https://youtu.be/wX4qozViCnI Lecture 11 - Reeinforcement Learning: https://youtu.be/aGmVbAlicw0 Lecture 12 - AI-Development: https://youtu.be/y31IMuHWvGU Lecture 13 - Guest Lecturer Rasmus Rothe: https://youtu.be/3uTFv6jEvFQ

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