Personal

[自分用]記事書きたいトピックまとめ

Weight Decay

https://qiita.com/supersaiakujin/items/97f4c0017ef76e547976
https://stats.stackexchange.com/questions/273189/what-is-the-weight-decay-loss/273190

Hololens

https://www.microsoft.com/ja-jp/hololens/apps/roboraid
https://qiita.com/guitar_char/items/0ed5c0dc36de596422d8
https://www.youtube.com/watch?v=jI0cIXskuY0

Wide&Deep Learning

https://qiita.com/Rowing0914/items/5df9666772d292fc2ab1
https://qiita.com/Rowing0914/items/65775f1a8b21c0a0de2f
https://qiita.com/nukky-s/items/3846fc658b325cdb2fa7

Training of RNN is difficult: explanation by Bengio!

http://ai.dinfo.unifi.it/paolo/ps/tnn-94-gradient.pdf

Distributed Tensorflow

tutorial
https://www.tensorflow.org/deploy/distributed
intuitive instruction
https://medium.com/clusterone/how-to-write-distributed-tensorflow-code-with-an-example-on-tensorport-70bf3306adcb

Software pattern Design

https://en.wikipedia.org/wiki/Software_design_pattern
https://qiita.com/ichi-nakashima/items/ee09c9341f85c18f748a
https://qiita.com/irxground/items/d1f9cc447bafa8db2388

Sphinx: efficient documentation tool

https://qiita.com/irxground/items/d1f9cc447bafa8db2388

Optimisation algorithms

http://cs231n.github.io/optimization-1/

NIPS research papers

https://papers.nips.cc/

TCP/IP/UDP

https://qiita.com/To_BB/items/f2a81fc72a5cdea7d159
http://www.atmarkit.co.jp/channel/tcpip/tcpip.html

machine learning on Arduino

https://www.quora.com/What-would-be-a-good-idea-for-a-project-to-apply-machine-learning-on-a-hardware-like-Arduino-microcontroller

MATLAB

official tutorial

CEH(Certified Ethical Hacker)

http://sokokara-security.blog.jp/archives/23239222.html
https://qiita.com/curryperformer-kato/items/245a7cf90f778a88415b

CTF: competition for white hackers

http://sandbox.spica.bz/cpaw_ctf/about_ctf.html
https://kimiyuki.net/blog/2016/12/02/getting-started-with-ctf/
https://qiita.com/curryperformer-kato/items/245a7cf90f778a88415b

IoT hacking and firmwares analysis

https://www.iotpentestingguide.com/chapter1.html
http://iotpentest.com/firmware-analysis-basics/
https://www.amazon.co.jp/IoT-Hackers-Handbook-Ultimate-Internet/dp/1974590127
http://ruffnex.net/iotsecjp/pdf/yuki/Yuki_SPI.pdf

Kali linux

Study guide: https://xeushack.com/best-books-for-learning-kali-linux/
Cook book: http://index-of.es/Varios/Packt.Kali.Linux.Network.Scanning.Cookbook.Aug.2014.ISBN.1783982144.pdf

Uniduino

https://assetstore.unity.com/packages/tools/input-management/uniduino-arduino-for-unity-6804
https://www.youtube.com/watch?v=qHMyHHf2LME

Introduction to Robotics

https://myenigma.hatenablog.com/entry/20150207/1423298357

handmade VR

https://github.com/relativty/Relativ
https://create.arduino.cc/projecthub/relativty/relativ-build-your-own-vr-headset-for-100-57adba

Motion Capture in Arduino without Kinetic ~MotionSuit~

https://www.youtube.com/watch?v=EmdWdiIL0is
https://hackaday.io/project/9266-motiosuit
https://github.com/alvaroferran/MotioSuit

Tensorflow Dev sum

https://www.analyticsvidhya.com/blog/2018/04/tensorflow-developer-summit-2018-highlights/

dialogue system on RNN

https://www.aclweb.org/anthology/N/N15/N15-1020.pdf
https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/46224.pdf

Find good projects for C++

Android OS dev?: http://1000projects.org/android-operating-system-a-c-project.html
Desktop application? : https://www.codeproject.com/KB/mcpp/
Algos?? : http://www.codeabbey.com/index/task_list

Inference Engines

https://www.microsoft.com/en-us/research/project/deep-reinforcement-learning-goal-oriented-dialogue/
wiki : https://ja.wikipedia.org/wiki/%E6%8E%A8%E8%AB%96%E3%82%A8%E3%83%B3%E3%82%B8%E3%83%B3

NLU:
https://www.microsoft.com/en-us/research/project/natural-language-understanding-nlu/

Stanford class: NLU
http://web.stanford.edu/class/cs224u/#
http://nbviewer.jupyter.org/github/cgpotts/cs224u/blob/master/vsm_02_dimreduce.ipynb
http://nbviewer.jupyter.org/github/cgpotts/cs224u/blob/master/vsm_03_retrofitting.ipynb
http://www.aclweb.org/anthology/N15-1184
https://github.com/mfaruqui/retrofitting

tensorflow workshop

https://ai.google/education#%3Fmodal_active=none
https://github.com/tensorflow/workshops