English DTU.dk Indeks Kontakt Telefonbog Alumnenetværk Portalen
 
 

Kursus

Deep Learning
Deep Learning
Institut
 DTU Compute
Fagområde
 Informatik og matematik
Kursets indhold
 Machine perception of natural signals has improved a lot in the recent years thanks to deep learning (DL). Improved vision systems with DL will make self-driving cars possible and is leading to more accurate image-based medical diagnosis. Improved speech recognition and natural language processing with DL will lead to many new intelligent applications within health-care and IT. Pattern recognition with DL in large datasets will give new tools for drug discovery, condition monitoring and many other data-driven applications. Applications in other areas such as natural language processing, biology, finance and robotics are numerous. Deep learning is an important tool for the leading IT companies' ambition about becoming machine learning and AI first companies.



The purpose of this course is to teach the participants about the latest developments in the field, about opportunities and pitfalls and give the participating companies access to computational frameworks that will allow them to go directly home and apply into in their own context. It covers both more well-established methods like feed-forward, convolutional and recurrent neural networks and frontiers like un-, semi- and reinforcement learning that can be expected to play a larger role in the coming years. The course is taught by Ole Winther, professor in Data science and complexity, DTU Compute, teaching assistants from DTU Compute with guest lecturers from companies using deep learning. Ole Winther is a deep learning machine learning researcher with experience in teaching deep learning both for DTU students and industry.
Deltagerprofil
 Target audience: The target audience is anyone who is interested in deep learning, who is comfortable with 1st year university math (linear algebra and basic probability) and with programming in Python or similar language.
Forudsætninger
 Programming preferably in Python, basic probability theory and basic linear algebra. Bring own laptop with web browser.
Kurset afholdes:
25-05-2020 09:00 - 29-05-2020 16:00
DTU Mødecenter
Anker Engelunds Vej 1, Bygn 101A
2800  Kgs. Lyngby

Jes Frellsenjefr@dtu.dk45253923DTU Compute
 
Sprog
 Engelsk
Kontaktperson
 Jes Frellsen  -  jefr@dtu.dk  -  45253923
Top
Anker Engelunds vej 1101 A2800 Kgs. LyngbyTlf. 45254525EAN-nr. 5798000430839