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Home Teaching Winter Semester 2018/19 Practical Course: Hands-on Deep Learning for Computer Vision and Biomedicine (10 ECTS)

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teaching:ws2018:dlpractice_ws2018 [2018/08/10 13:02]
Vladimir Golkov
teaching:ws2018:dlpractice_ws2018 [2019/01/22 10:29] (current)
Vladimir Golkov
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 ===== Winter Semester 2018/2019, TU München ===== ===== Winter Semester 2018/2019, TU München =====
 +
 +<​html>​
 +<font color="​red"​ size="​4"><​b>​
 +This is the winter semester 2018/2019 course. For the summer semester 2019 course, see
 +</​html>​
 +[[teaching:​ss2019:​dlpractice_ss2019|here]].
 +<​html>​
 +</​b></​font>​
 +</​html>​
  
 **Please direct all questions regarding this practical course to golkov[at]in.tum.de**\\ **Please direct all questions regarding this practical course to golkov[at]in.tum.de**\\
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 There will be three lectures in the beginning of the semester.\\ There will be three lectures in the beginning of the semester.\\
 Time: Tuesdays 2-4pm\\ Time: Tuesdays 2-4pm\\
-Room: 03.13.010+Room: [[https://​portal.mytum.de/​displayRoomMap?​roomid=03.13.010@5613&​disable_decoration=yes|03.13.010]]
  
 16 October: Machine Learning; Artificial Neural Networks; Network Training; Convolutional Neural Networks\\ 16 October: Machine Learning; Artificial Neural Networks; Network Training; Convolutional Neural Networks\\
 23 October: Recap; Network Architecture Design; Understanding and Visualizing\\ 23 October: Recap; Network Architecture Design; Understanding and Visualizing\\
 30 October: Recap; Programming;​ Evaluating\\ 30 October: Recap; Programming;​ Evaluating\\
-6 November: Q&A\\+6 November: Q&​A ​about Deep Learning\\
  
 //Note: ECTS credits are the measure of workload. So-called semester weekly hours (Semesterwochenstunden,​ SWS) are NOT a measure of project work time, but merely of classroom time.// ​ //Note: ECTS credits are the measure of workload. So-called semester weekly hours (Semesterwochenstunden,​ SWS) are NOT a measure of project work time, but merely of classroom time.// ​
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   * [[http://​www.mlyearning.org/​|Ng:​ Machine Learning Yearning]]   * [[http://​www.mlyearning.org/​|Ng:​ Machine Learning Yearning]]
   * [[http://​neuralnetworksanddeeplearning.com/​|Nielsen:​ Neural Networks and Deep Learning]]   * [[http://​neuralnetworksanddeeplearning.com/​|Nielsen:​ Neural Networks and Deep Learning]]
 +  * [[https://​arxiv.org/​abs/​1206.5533|Y. Bengio: Practical Recommendations]]
  

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