2020-02-14 04:00 分まとめ(35件)

カテゴリー	サイト名	記事タイトル	リンクURL	頻出ワード・要約等	登録日
金融	金融庁ホームページ	「違法な金融業者に関する情報について」を更新しました。	https://www.fsa.go.jp/ordinary/chuui/index.html		2020-02-10 17:00:00
金融	金融庁ホームページ	「違法な金融業者に関する情報について」を更新しました。	https://www.fsa.go.jp/ordinary/chuui/index.html		2020-02-10 17:00:00
python	Pythonタグが付けられた新着投稿 - Qiita	pandasで動的に新たなデータフレームを作る	https://qiita.com/c_c_c_c/items/9aa8d43140f59bfe62c7	perlRubyJSあたりの、自由な辞書構造の感覚で、pandasを扱いたいときに、どうしてもキーindexがないという問題になるように思います。まず、AAAhogeilocnhogehogeみたいな発想を一度捨てるところから始まります。	2020-02-14 03:12:49
js	JavaScriptタグが付けられた新着投稿 - Qiita	TensorFlow.jsを使ってjavascript上でkerasモデルを使う	https://qiita.com/studio_haneya/items/00311534d6fc9a32b570	python版tensorflowで作ったmodelを変換するpython版のモデルを用意するmodelsaveで保存したhファイルを変換することが出来ます。ただし、ブラウザ上で動作するjavascriptはローカルのファイルを読めなくなっているので、面倒ですが適当なウェブサーバーを立ててドキュメントルート以下に上記で変換したモデルをフォルダごと置いてブラウザでURLを読み込むようにします。	2020-02-14 03:33:30
海外TECH	Ars Technica	What the CEO of Epic Games gets wrong about video games and politics	https://arstechnica.com/?p=1653639	games	2020-02-13 18:17:11
Apple	AppleInsider - Frontpage News	Lowest price ever: Apple's 8-core 15" MacBook Pro just $2,149, plus up to $500 off 13" models	https://appleinsider.com/articles/20/02/13/lowest-price-ever-apples-8-core-15-macbook-pro-just-2149-plus-up-to-500-off-13-models	Available exclusively for AppleInsider readers B amp H Photo is slashing the price of Apple s Mid inch MacBook Pro that s packed with upgrades dropping it to a record low Save on the high end config with an core processor extra storage and upgraded graphics or snap up hundreds of dollars in savings on inch MacBook Pro models	2020-02-13 18:49:03
Apple	AppleInsider - Frontpage News	Machine learning could help Apple Maps fix bogus GPS coordinates	https://appleinsider.com/articles/20/02/13/machine-learning-could-help-apple-maps-fix-bogus-gps-coordinates	Apple Maps may be able to provide its users with more accurate information about their location in the future by using artificial intelligence to adjust GPS data when incorrect information or mistakes are detected in sensor readings	2020-02-13 18:38:09
海外TECH	Network World	IT Salary Survey 2020: The results are in	https://www.idginsiderpro.com/article/3526496/it-salary-survey-2020-the-results-are-in.html#tk.rss_all	specialties	2020-02-13 18:11:00
海外科学	NYT > Science	Coronavirus Live Updates: China Expands Mass Roundup	https://www.nytimes.com/2020/02/13/world/asia/china-coronavirus.html?emc=rss&partner=rss	hubei	2020-02-13 18:36:34
海外科学	BBC News - Science & Environment	Human brain parts left over from surgery boosts research	https://www.bbc.co.uk/news/science-environment-51363582	boosts	2020-02-13 18:03:53
金融	金融庁ホームページ	金融審議会「市場ワーキング・グループ」（第27回）議事次第を公表しました。	https://www.fsa.go.jp/singi/singi_kinyu/market_wg/siryou/20200213.html	金融審議会	2020-02-13 20:00:00
ニュース	@日本経済新聞 電子版	@nikkei ロシア、領土割譲の禁止検討　改憲案で ...	https://twitter.com/nikkei/statuses/1228026049931313153	nikkei	2020-02-13 19:40:00
海外ニュース	Japan Times latest articles	Roki Sasaki’s first bullpen session draws raves reviews from former major leaguers on Lotte staff	https://www.japantimes.co.jp/sports/2020/02/13/baseball/japanese-baseball/roki-sasakis-first-bullpen-session-draws-raves-reviews-former-major-leaguers-lotte-staff/	bullpen	2020-02-14 04:53:37
海外ニュース	Japan Times latest articles	NFL team’s deep Catholic ties behind role in abuse crisis	https://www.japantimes.co.jp/sports/2020/02/13/more-sports/football/nfl-teams-deep-catholic-ties-behind-role-abuse-crisis/	church	2020-02-14 04:54:55
海外ニュース	Japan Times latest articles	Hong Kong, Singapore rugby sevens events postponed due to coronavirus	https://www.japantimes.co.jp/sports/2020/02/13/rugby/hong-kong-singapore-rugby-sevens-events-postponed-due-coronavirus/	rugby	2020-02-14 04:54:02
海外ニュース	Japan Times latest articles	Hawks’ ambitious project with Carter Stewart could spark huge changes	https://www.japantimes.co.jp/sports/2020/02/13/baseball/japanese-baseball/hawks-ambitious-project-carter-stewart-spark-huge-changes/	fukuoka	2020-02-14 03:53:52
ニュース	BBC News - Home	US-Taliban talks: Pompeo hails 'pretty important breakthrough'	https://www.bbc.co.uk/news/world-asia-51494921	donald	2020-02-13 18:23:09
ビジネス	ダイヤモンド・オンライン - 新着記事	1銘柄で利益1億円を超えた 「北の達人」 - 10万円から始める！　小型株集中投資で1億円	https://diamond.jp/articles/-/227270		2020-02-14 04:00:00
ビジネス	ダイヤモンド・オンライン - 新着記事	なぜバリスタは毎回、美味しいコーヒーを 淹れられるのか？　「秘伝の方程式」を公開 - ワールド・バリスタ・チャンピオンが教える 世界一美味しいコーヒーの淹れ方	https://diamond.jp/articles/-/227072	嵐にしやがれ	2020-02-14 03:55:00
ビジネス	ダイヤモンド・オンライン - 新着記事	僕が学生時代に とても感銘を受けた 2冊の古書 - 哲学と宗教全史	https://diamond.jp/articles/-/222240		2020-02-14 03:45:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【山口周×塩田元規×箕輪厚介】 大事な意思決定こそ「頭」ではなく「心」で決めろ！ - ニュータイプの時代　新時代を生き抜く24の思考・行動様式	https://diamond.jp/articles/-/226680	意思決定	2020-02-14 03:40:00
ビジネス	ダイヤモンド・オンライン - 新着記事	怒りっていうのは、 「相手が期待通りじゃなかった」 ときにでてくるのよね。 だから、期待しなければ 怒らないで済む。 - 精神科医Tomyが教える　１秒で不安が吹き飛ぶ言葉	https://diamond.jp/articles/-/227613	twitter	2020-02-14 03:35:00
GCP	Cloud Blog	How Udacity students succeed with Google Cloud	https://cloud.google.com/blog/topics/customers/how-udacity-uses-google-cloud/	Editor s note Today we hear from Udacity which uses a variety of Google Cloud technologies for its online learning platform Read on to learn how they built online workspaces that give students immediate access to fast isolated compute resources and private data sets   At Udacity we use advanced technologies to teach about technology One example is our   interactive “ Workspaces which students use to gain hands on experience with a variety of advanced topics like artificial intelligence data science programming and cloud These online environments comprise everything from SQL interpreters to coding integrated development environments IDEs Jupyter Notebooks and even fully functional D graphical desktops ー all accessible via an everyday browser Udacity s latest IDE environment “ uLab where “ Learning Guides can demonstrate skills interactively To build these Workspaces we relied heavily on Google Cloud Platform GCP in numerous interesting and novel ways This article details our implementation and where we hope to take it in the future   Workspaces design goalsUdacity customers are smart busy learners from all over the world who access our courses remotely To meet their needs we designed Udacity Workspaces to Be ready to use in under secondsOffer advanced functionality directly inside the browser based Udacity ClassroomInstantly furnish starter and example files to students in a new Workspace and automatically save all student work and progress for the next sessionProvide quick access to large external datasetsFunction well with any session duration … from two minutes to four hours or moreProvide reliable compute availability and GPU power wherever neededWe chose GCP for its ease of use reliability and cost effectiveness Let s see how we used different GCP offerings to meet these goals Fast personalized access to Workspaces   Students demand immediate access to their Workspaces but booting up a full GCP host from an image can take awhile That s OK if a student plans on using their Workspace for an hour but not if they re using it for a two minute Workspace coding challenge To address this we built a custom server management tool “ Nebula that maintains pools of ready servers to assign to students immediately To control costs the pools are sized by a custom usage pressure measurement algorithm to be fairly surge ready but which also reduces the pools to as small as a single instance during idle periods Pools are maintained in multiple data centers to maximize access to GPUs GCP s by the second pricing and flexible reservations policy served us well here Given the short usage windows of some student exercises hourly billing or bulk billing might have proved cost prohibitive Having ready to go server pools minimizes startup time but we also needed to place “ starter files or later on the student s own work from a previous session onto the hosts as quickly as possible After experimenting with several approaches we decided to store these files as tarballs in Cloud Storage We found that we can copy up to GB to and from Cloud Storage within our SLA time window so we set a hard limit of GB for student drives Every time a student s session goes idle for half an hour we deallocate the host compress and copy the student s files to Cloud Storage then delete the host In this manner we make time stamped backups of each session s files that students can opt to restore any time they need to via the Workspaces GUI An alternative approach could be to leverage Cloud Storage s version control which provides access to GCP slifecycle controls as well However at the time we built the student files storage system this GCP feature was still in beta so we opted for a home grown facility In addition we take advantage of Cloud Functions to duplicate the student files in a second region to ensure against regional outages Side note if we were to build this feature today we could take advantage of dual region buckets to automatically save student files in two regions Access to large datasetsFrom time to time students need to access large datasets e g in our machine learning courses Rather than writing these datasets on server images we mount read only drives to share a single dataset across multiple student hosts We can update these datasets on new shared drives and Nebula can point new sessions at these new drives without interrupting existing session mounts   To date we ve never run into a concurrent read only mount limit for these drives However we do see a need for quick mount read write dataset drives One example could be a large SQL database that a student is expected to learn to modify in bulk Duplicating a large drive on the fly isn t feasible so one approach could be to manage a pool of writeable drive copies to mount just in time or to leverage Google Cloud s Filestore   With the Filestore approach you d pre create many copies of data drives in a folder tree and mount a particular folder on the Filestore to a specific student s container when access is needed that copy would then never be assigned to anybody else and asynchronously deleted replaced with a fresh unaltered copy when the student s work is finished Consistent compute powerIn a shared environment e g Google Kubernetes Engine one student s runaway process could affect the compute performance of another student s entire container on the same metal To avoid that we decided on a “ one server per student model where each students gets access to a single Compute Engine VM running several Docker containers ー one container for the student s server another for an auto grading system and yet another for handling file backups and restores In addition to providing consistent compute power this approach also has a security advantage it allows us to run containers in privileged mode say to use specialized tools without risking a breach beyond the single VM allocated to any one student This architecture also ensures that GPU equipped hosts aren t shared either so students benefit from all available performance This is especially important as students fire up long running compute intensive jobs such as performing image recognition   As a cost control measure we meter GPU host usage and display available remaining GPU time to students so they   switch their GPUs on and off This “ switching actually allocates a new host from our pools to the student either GPU enabled or not Because we can do the switch in under seconds it feels approximately like a toggle switch but some aspects of the session such as open files may be reset e g in an IDE configuration We encourage students to ration their GPU time and perform simpler tasks such as editing or file management in “ CPU mode One of our GPU host configurations provides an in browser Ubuntu desktop with pass through Nvidia K GPUs for high performance compute and graphics This configuration is heavily employed by our Autonomous Systems students who run graphics intensive programs like Gazebo shown and run robot environment simulations You can read more about this configuration here Wanted flexible and isolated imagesThis configuration has hit all our goals except for true image flexibility For our large variety of courses we require many variations of software installations Normally such needs would be satisfied with containers but the requirement of isolated compute environments eliminates that as an option   In the past two years we ve empowered hundreds of thousands of Udacity students to advance their careers and learn new skills with powerful learning environments called Workspaces built on top of GCP Throughout GCP has proven itself to be a robust platform and a supportive partner and we look forward to future product launches on top of Google Cloud If you d like to learn more about the solutions we ve built feel free to reach out to me on Twitter Atlas	2020-02-13 19:00:00