Loading...
ÀΰøÁö´É¸Ó½Å¿¬±¸È¸ 2017³âµµ ¼­¸Ó½ºÄð

* µî·Ï ¸¶°¨ µÇ¾ú½À´Ï´Ù *


´ëÇѱâ°èÇÐȸ ÀΰøÁö´É¸Ó½Å¿¬±¸È¸ 2017³âµµ ¼­¸Ó½ºÄð °³ÃÖ ¾È³»

´ëÇѱâ°èÇÐȸ ȸ¿ø ¿©·¯ºÐ,

´ëÇѱâ°èÇÐȸ ÀΰøÁö´É¸Ó½Å¿¬±¸È¸¿¡¼­´Â ´ÙÀ½°ú °°Àº ÀÏÁ¤À¸·Î ±â°èÇнÀ, µö·¯´× ¹× °­È­ÇнÀ¿¡ ´ëÇÑ ¼­¸Ó½ºÄðÀ» °³ÃÖÇÕ´Ï´Ù. ±Ý¹ø ±³À°¿¡¼­´Â ±â°è ºÐ¾ß¿¡ ƯȭµÈ À̷аú ½Ç½ÀÀ» ÁøÇàÇÒ ¿¹Á¤ÀÌ¿À´Ï, ȸ¿ø ¿©·¯ºÐÀÇ ¸¹Àº Âü¿©¸¦ ºÎŹµå¸³´Ï´Ù.

¢Â Çà »ç ¸í : ÀΰøÁö´É¸Ó½Å¿¬±¸È¸ 2017³âµµ ¼­¸Ó½ºÄð

¢Â °³ÃÖÀÏÀÚ : 2017³â 8¿ù 21ÀÏ(¿ù) ~ 8¿ù 23ÀÏ(¼ö) 3ÀÏ°£

¢Â °³ÃÖÀå¼Ò : Çѱ¹°úÇбâ¼úȸ°ü ¼ÒȸÀǽÇ2(¼­¿ï½Ã °­³²±¸ ¿ª»ïµ¿)

¢Â ÇÁ·Î±×·¥ : 

ÀÏÀÚ

½Ã°£

³»¿ë

°­»ç

8. 21.(¿ù)

10:00~13:00

±â°èÇнÀÀÇ ±âÃÊ

¿ÀÇö¼® ±³¼ö(GIST)

14:00~18:00

µö·¯´× ÀÌ·Ð

À̽Âö ±³¼ö(UNIST)

8. 22.(È­)

09:00~13:00

µö·¯´× ÀÌ·Ð/½Ç½À

À̽Âö ±³¼ö(UNIST)

14:00~18:00

µö·¯´× ½Ç½À

À̽Âö ±³¼ö(UNIST)

8. 23.(¼ö)

09:00~13:00

°­È­ÇнÀ ÀÌ·Ð

ÀÌ´öÁø ±³¼ö(±º»ê´ë)

14:00~18:00

°­È­ÇнÀ ÀÌ·Ð/½Ç½À

ÀÌ´öÁø ±³¼ö(±º»ê´ë)

¢Â °­ÀÇ ³»¿ë ¼Ò°³

Á¦¸ñ

³»¿ë

±â°èÇнÀÀÇ ±âÃÊ

- Introduction to Machine Learning, Regression Analysis, Naive Bayesian Classifier, Hidden Markov Model, K-means Dlustering, Support Vector Machine, Neural Networks

µö·¯´×
(Deep Learning)

- ÀÌ·Ð : Neural Networks, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Autoencoder
- ½Ç½À : MNIST Data, Áøµ¿µ¥ÀÌÅÍ, À½Çâµ¥ÀÌÅÍ
- µ¥¸ð : CNN & RNN in Raspberry Pi
- ½Ç½À S/W : TensorFlow

°­È­ÇнÀ
(Reinforcement Learning ; RL)

- ÀÌ·Ð : ½ÉÃþÇнÀ ÃֽŠ°æÇâ,  RL ±âº» °³³ä, Q-Learning, ½ÉÃþ°­È­ÇнÀ, Deep Q-Learning
- ½Ç½À : Q-Learning, Deep Q-Learning,
- µ¥¸ð : ÀÚÀ²ÁÖÇà ½Ã¹Ä·¹À̼Ç
- ½Ç½À S/W : Python, TensorFlow, Theano

* ½Ç½À °ü·Ã ¾È³» »çÇ×
- ½Ç½ÀÀ» ¿øÇϽô ºÐÀº °³º° ³ëÆ®ºÏÀ» ÁöÂüÇÏ¿©¾ß ÇÕ´Ï´Ù.
- ÇÊ¿äÇÑ ÇÁ·Î±×·¥ ¼³Ä¡´Â µî·ÏÇÑ ºÐ¿¡°Ô¸¸ ¸ÞÀÏ·Î 8¿ù 17ÀÏ°æ ¼ÛºÎÇØ µå¸± ¿¹Á¤ÀÔ´Ï´Ù.

* °­ÀÇ·Ï
- °­ÀÇ ½Ã¿¡ Ã¥ÀÚ·Î ¹èºÎÇØ µå¸± ¿¹Á¤ÀÔ´Ï´Ù.

¢Â µî·Ï ¾È³»

1. µî·Ï Á¢¼ö ¸¶°¨ : 8¿ù 11ÀÏ(±Ý)±îÁö ¢Ñ [µî·Ï ¹Ù·Î°¡±â]
* Á¤¿ø ÃÊ°ú ½Ã Á¶±â¿¡ ¸¶°¨µÉ ¼ö ÀÖ½À´Ï´Ù.

2. µî·Ïºñ

ÀϹÝ

Çлý

ȸ¿ø

ºñȸ¿ø

ȸ¿ø

ºñȸ¿ø

300,000

350,000

200,000

230,000

3. µî·Ïºñ ³³ºÎ¹æ¹ý
¢Å ÀºÇàÀ» ÀÌ¿ëÇÑ ³³ºÎ¹æ¹ý
: Çѱ¹¾¾Æ¼ÀºÇà / ¿¹±ÝÁÖ ´ëÇѱâ°èÇÐȸ / 186-02900-245-01
¢Å Ä«µå ¹× °èÁÂÀÌü ÀÌ¿ëÇÑ ³³ºÎ¹æ¹ý: »çÀüµî·Ï ÆäÀÌÁö¿¡¼­ ÀüÀÚ°áÁ¦½Ã½ºÅÛ ÀÌ¿ë

¢Â Çà»ç ¹®ÀÇ
   ´ëÇѱâ°èÇÐȸ ¹Ú±â¼­ ½ÇÀå(02-501-5035, manage@ksme.or.kr)

ÀΰøÁö´É¸Ó½Å¿¬±¸È¸ ȸÀå / ´ëÇѱâ°èÇÐȸ ºÎȸÀå ¼Û Àç º¹

(»ç)´ëÇѱâ°èÇÐȸ
´ëÇ¥ÀÚ: ±èµ¿È¯ ¤Ó °íÀ¯¹øÈ£ : 220-82-01671 l [06130] ¼­¿ï½Ã °­³²±¸ Å×Çì¶õ·Î 7±æ 22 Çѱ¹°úÇбâ¼úȸ°ü 1°ü 702È£,
Tel : (02) 501 - 3646, 3647, 3648, 5305, 5035, 6046, 6056, 6061 l FAX:(02) 501-3649 l E-mail : ksme@ksme.or.kr
´ã´ç/¹®ÀÇó