投稿時間:2021-06-13 22:30:07 RSSフィード2021-06-13 22:00 分まとめ(33件)

カテゴリー等	サイト名等	記事タイトル・トレンドワード等	リンクURL	頻出ワード・要約等/検索ボリューム	登録日
python	Pythonタグが付けられた新着投稿 - Qiita	Marqeta使ってみた（その1）	https://qiita.com/yazn/items/d6fd767f3a3932e6afc6	Marqeta使ってみたその先日IPOしたばかりのMarqetaプラットフォームを使ってみました。	2021-06-13 21:50:50
python	Pythonタグが付けられた新着投稿 - Qiita	PythonからPostgreSQLを操作	https://qiita.com/from_chc/items/b903720abeabfe67c502		2021-06-13 21:04:21
js	JavaScriptタグが付けられた新着投稿 - Qiita	輪読メモ｜JavaScript｜applyとcallとbindのthisの対象についての確認	https://qiita.com/nononosuque/items/d3d4150636528f5e0ea3	KANSUSIKIapplyzzz→ZZZ xyKANSUSIKIcallzzz→ZZZ xyKANSUSIKIbindzzzƒconsolelogthisKANSUSIKIbindzzz→ZZZ xyアロー関数でapplyもcallもbindを確認してみる出力ログからwindowオブジェクトを参照していることが分かるため、引数として渡しているthisは利用されていないことが分かります。	2021-06-13 21:25:05
js	JavaScriptタグが付けられた新着投稿 - Qiita	Denoで「自身のファイルからの相対パス」	https://qiita.com/access3151fq/items/233bd3d72f62ad684fa1	Denoで「自身のファイルからの相対パス」相対パスでのファイル操作について。	2021-06-13 21:16:28
js	JavaScriptタグが付けられた新着投稿 - Qiita	vue-realworld-example-appを読んでみた	https://qiita.com/JetNel0/items/8fdc09f5146467524ca0	アプリ全体の設定などはここで行う。	2021-06-13 21:15:40
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	cat - > tmp の意味	https://teratail.com/questions/343835?rss=all	catgttmp	2021-06-13 21:59:03
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	returnでawaitしてもしなくてもいいのか	https://teratail.com/questions/343834?rss=all	async	2021-06-13 21:58:48
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	golang*nginxでgolangでリダイレクトさせたらパラメーターがつかない	https://teratail.com/questions/343833?rss=all	golangnginxでgolangでリダイレクトさせたらパラメーターがつかないGoGinとnginxで外部にパラメーター付きでリダイレクトさせたいツイッターでログインさせようとしています。	2021-06-13 21:53:55
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	あるときだけJavaScriptがエラーになります。	https://teratail.com/questions/343832?rss=all	ある とき だけ JavaScript が エラー に なり ます 。	2021-06-13 21:51:36
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	onclickが反応しない	https://teratail.com/questions/343831?rss=all	onclickが反応しない前提・実現したいことここに質問の内容を詳しく書いてください。	2021-06-13 21:51:09
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	GASからLIVEDOOR BLOGにAPIを使って記事を投稿したい。	https://teratail.com/questions/343830?rss=all	GASからLIVEDOORBLOGにAPIを使って記事を投稿したい。	2021-06-13 21:44:26
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	java Mapでkeyの前方一致とvalueの文字列の含まれるもの	https://teratail.com/questions/343829?rss=all	javaMapでkeyの前方一致とvalueの文字列の含まれるもの前提・実現したいことjavaでmapを使い、keyの前方一致、valueは文字が含まれるのを検索するプログラムを作っています。	2021-06-13 21:36:04
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	数値からなるリストに対して、割合にして返す関数の作成について	https://teratail.com/questions/343828?rss=all	isvoutforiinrangelenlisv	2021-06-13 21:34:13
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	特定期間の西暦年と昭和年の対応表を作る	https://teratail.com/questions/343827?rss=all	特定期間の西暦年と昭和年の対応表を作る標準入力から、行目に西暦年、行目に年数が与えられます。	2021-06-13 21:21:13
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	404 Not Foundエラーが発生してしまう	https://teratail.com/questions/343826?rss=all	NotFoundエラーが発生してしまうエラーnbspNotnbspFoundエラーが出てしまいます。	2021-06-13 21:12:29
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	標準入力とfor文の組み合わせ	https://teratail.com/questions/343825?rss=all	組み合わせ	2021-06-13 21:07:27
Ruby	Rubyタグが付けられた新着投稿 - Qiita	Marqeta使ってみた（その1）	https://qiita.com/yazn/items/d6fd767f3a3932e6afc6	Marqeta使ってみたその先日IPOしたばかりのMarqetaプラットフォームを使ってみました。	2021-06-13 21:50:50
Ruby	Rubyタグが付けられた新着投稿 - Qiita	Rails初学者によるRailsチュートリアル学習記録⑭ 第12章	https://qiita.com/UtimoriNI/items/97d51533e64b2233a2ca	アカウントの有効化の機能では、メール内のリンクをクリックしたタイミングで、データベース内の有効化ステータスを変更したかったので、editアクションのみを使用しましたが、今回はフォームを生成する必要があるのでnewアクションも使用します。	2021-06-13 21:29:47
AWS	AWSタグが付けられた新着投稿 - Qiita	TerraformとCognitoとVue.jsで認証機能付きサーバレスWebアプリを構築する	https://qiita.com/neruneruo/items/092f1789e37d9358114d	Vuejsの基本APIGatewayにおけるCORSの対応Sの静的コンテンツのウェブサイトホスティングの基本やりたいこと構成図今回はシンプルに作るため、未認証時にはログイン画面を表示し、あらかじめCognitoに登録しているユーザIDで認証をしたら、該当ユーザの情報をDynamoDBから取得して画面に表示するといった簡単なアプリにする。	2021-06-13 21:42:34
Docker	dockerタグが付けられた新着投稿 - Qiita	開発環境と本番環境を分けたい	https://qiita.com/suama-akdo5317/items/e1d0c8dc38ec3fcf11c5	dockercompose	2021-06-13 21:17:17
GCP	gcpタグが付けられた新着投稿 - Qiita	【GCP】組織ポリシー VS. Dataflow VS. Private Google Access	https://qiita.com/sabawanco/items/0962b9c37d7a1e4db8de	この設定でジョブを実行すると・・・ジョブが成功しましたまとめ外部IPを制限する組織ポリシーを入れた環境でDataflowを動かすことができました。	2021-06-13 21:10:08
Azure	Azureタグが付けられた新着投稿 - Qiita	【続】SORACOM x Nerves できたとはいえるとぼくおもいます	https://qiita.com/torifukukaiou/items/efe528f8dbd1012ba37e	【続】SORACOMxNervesできたとはいえるとぼくおもいますはじめにElixir楽しんでいますか先日、「SORACOMxNervesできたとはいえるとぼくおもいます」と書きました進展がありましたので書いておきますこの記事は、土月開催のautoracexというElixirのもくもく会での成果ですこの記事で書いていることSORACOMAirforセルラーのSIMをセットしたLCをNervesがイゴいているRaspberryPiに挿してセルラー通信を楽しみますnervesprojectnervessystemrpiをカスタマイズします本当に、SORACOMAirforセルラーでセルラー通信していることを確かめるために、SORACOMBeamを使いますponコマンドやiprouteコマンドなどを使って多少強引ではありますがセルラー通信ができるようになりましたたったのステップです①準備②SIMの購入・データ通信端末の購入③CustomizingYourOwnNervesSystem④RunSORACOMBeamとは、図を拝借させていただきましたSORACOMBeam以下、Beamは、IoTデバイスにかかる暗号化等の高負荷処理や接続先の設定を、クラウドにオフロードできるサービスです。	2021-06-13 21:34:33
Ruby	Railsタグが付けられた新着投稿 - Qiita	Rails初学者によるRailsチュートリアル学習記録⑭ 第12章	https://qiita.com/UtimoriNI/items/97d51533e64b2233a2ca	アカウントの有効化の機能では、メール内のリンクをクリックしたタイミングで、データベース内の有効化ステータスを変更したかったので、editアクションのみを使用しましたが、今回はフォームを生成する必要があるのでnewアクションも使用します。	2021-06-13 21:29:47
技術ブログ	Developers.IO	[AWS CDK] CloudFrontの標準ログ（アクセスログ）をS3バケットに出力する	https://dev.classmethod.jp/articles/output-cloudfront-access-logs-to-s3-bucket-with-aws-cdk/	amazon	2021-06-13 12:10:33
海外TECH	DEV Community	10 Deep Learning Projects (Beginner & Advanced)	https://dev.to/python_engineer/10-deep-learning-projects-beginner-advanced-1ad2	Deep Learning Projects Beginner amp Advanced Here are deep learning projects from beginner to advanced that you can do with TensorFlow or PyTorch For each project the links to the datasets are included MNISTThe MNIST dataset is a large set of handwritten digits and the goal is to recognize the correct digit This project is fairly easy it should make you comfortable with your deep learning framework and you should learn how you can implement and train your first Artificial Neural Network It also teaches you how to do multiclass classification problems instead of just binary problems MNIST can be loaded directly from within TensorFlow and PyTorch CIFAR This project is similar but a little bit more difficult than the first one It contains color images of different classes like airplanes birds dogs and other objects Here it s a little bit harder to get a good classification model Now instead of just using a simple neural net you should implement a Convolutional Neural Net and learn how they work CIFAR can be loaded directly from within TensorFlow and PyTorch Dogs vs CatsThe third project is the Dogs vs Cats challenge on Kaggle As the name suggests the dataset only contains images of either a dog or a cat This classification task is actually a little bit simpler than in the previous task because now we only deal with a binary classification problem But the challenging part could be to learn how to download the data and load it with the correct format into your model If you are ambitious you can then submit your results to Kaggle and compete with other people To get a really good performance you could also have a look at a technique that is called Transfer Learning This is a very important concept that you should learn sooner or later so now would be a good point to try this If you want to learn more about this then I have a tutorial for you here Dogs vs Cats Kaggle Breast Cancer ClassificationThe medical field is one of the most common use cases of deep learning There are many applications out there that help to detect diseases and help physicians to make their diagnosis Here you can help to improve these applications and bring your knowledge to a good use The particular project I selected for beginners is about Breast Cancer Classification Here you have to train a model to classify cancer subtypes based on D Medical Histopathology images Breast cancer is the most common form of cancer in women and accurately identifying and categorizing breast cancer subtypes is an important clinical task If you can come up with a reliable automated method here then this can be used to save time and reduce errors in hospitals Breast Cancer Classification Breast Histopathology Images Kaggle Natural Language Processing with Disaster TweetsUp until now we had four computer vision projects Now let s switch the field and have a look at Natural Language Processing or short NLP This is another field where deep learning is widely used Here we don t deal with images but instead with words and sentences To get started I recommend the Disaster Tweet project Again you find this on Kaggle in the NLP getting started category You have to classify Twitter Tweets and predict if they are about real disasters or not This would be a nice time to learn about RNNs Recurrent Neural Networks and LSTMs Long Short Term Memory These are two special types of neural networks that are extremely important when working with text data You can find a tutorial about them here Natural Language Processing with Disaster Tweets Kaggle ChatbotNext I suggest a project I think almost everyone will enjoy And this is about chatbots Build your own chatbot from scratch and put it to test with a simple chat application To get data for this task I can point you to two large open source datasets which should be enough for the beginning The first is the Conversational Question Answering dataset provided by Stanford NLP and the other one is the Google Natural Questions dataset If you don t know how to get started then I can point you to my tutorial where we build a simple chatbot with an RNN together Once you ve understood the concepts of RNNs then creating a maybe not advanced but decent chatbot is not that hard anymore Google s Natural QuestionsCoQA A Conversational Question Answering Challenge Recommender SystemNow let s go to a task almost every company needs Have a look at Netflix YouTube Instagram Spotify and all the other big names They all need Recommender Systems Based on the information they collect on each user they want to recommend other content that the user might enjoy To get started with this I suggest to build a movie recommender system You can either use the MovieLens K Dataset or the official Netflix dataset on Kaggle This is also a good time to learn about a technique that is called collaborative filtering You could solve this with „classical“Data Science techniques but you can also build deep recommender systems using deep learning MovieLens K DatasetNetflix Prize data Kaggle ForecastingNext let s have a look at Forecasting This is another interesting field where we deal with a time series and you can practice your knowledge about RNNs again We want to predict the values of a time series in the future A very popular example for this is stock price prediction As dataset here I actually encourage you to scrape or download the stock data yourself from Yahoo Finance This should not be too hard and there is also a python package yfinance that you can simply use So get some stock data use the time data only up to a certain point in the past to train your model then see how it predicts the prices from the rest of the data up to the present time and then build a system to predict the prices in the future Yahoo financeyfinance Python Package Object DetectionThe last two projects are advanced Computer Vision tasks First let s have a look at Object Detection The goal is to identify the specified objects and mark the positions in the image So you have to check if there is an object and then where it is and also deal with possible multiple objects in an image This is indeed a very advanced task and you could try to recreate the popular YOLO object detection model from scratch but I recommend to just use a pertained model Then you still have to implement the whole object detection pipeline and you should learn about OpenCV here A very important Computer Vision library that is used here for example to draw the bounding boxes As datasets I can point you to the Raccoon dataset or the Annotated Driving Dataset that is used for self driving cars Raccoon DatasetAnnotated Driving DatasetHelpful Articles Towardsdatascience Build Your Own Object DetectorTowardsdatascience Object Detection With TensorFlow Object Detector API Style TransferAs last project I suggest to have a look at style transfer a very interesting use of deep learning You train a model and can then feed a style image to this model and after training it is able to apply this style to any other given image you want Here again you don t have to implement this from scratch but can use an existing framework like the TensorFlow fast style transfer or the PyTorch fast neural style implementation To retrain your model for your own style images you should use the COCO dataset COCO is a large scale object detection segmentation and captioning dataset and it s one of the most important deep learning datasets for computer vision that you should definitely check out TensorFlow Fast Style TransferPyTorch Fast Neural StyleCOCO dataset Final WordsI hope you will enjoy these projects And if you need help you can always join our community in the Discord server	2021-06-13 12:41:15
海外TECH	DEV Community	Clippy in VSCode 😱	https://dev.to/adam_cyclones/clippy-in-vscode-4291	clippy	2021-06-13 12:29:45
海外ニュース	Japan Times latest articles	Kokoro Kageura and Sara Asahina claim heavyweight wins at worlds	https://www.japantimes.co.jp/sports/2021/06/13/more-sports/judo/kageura-asahina-worlds/	Kokoro Kageura and Sara Asahina claim heavyweight wins at worldsKageura broke a world championship drought for Japan in the men s over kilogram division dating back to by defeating Russia s Tamerlan Bashaev in the	2021-06-13 21:09:43
ニュース	BBC News - Home	G7 summit: Dominic Raab says EU's attitude to Northern Ireland 'offensive'	https://www.bbc.co.uk/news/uk-politics-57460077	country	2021-06-13 12:01:53
ニュース	BBC News - Home	Euro 2020: Excitement builds as England face Croatia in opening game	https://www.bbc.co.uk/news/uk-57460595	trafalgar	2021-06-13 12:31:53
ニュース	BBC News - Home	French Open champion Krejcikova completes rare double	https://www.bbc.co.uk/sport/tennis/57460937	singles	2021-06-13 12:02:56
ニュース	BBC News - Home	Euro 2020: BBC pundits wish Christian Eriksen all the best in his recovery	https://www.bbc.co.uk/sport/av/football/57461410	Euro BBC pundits wish Christian Eriksen all the best in his recoveryGary Lineker Alan Shearer Frank Lampard and Rio Ferdinand speak of their relief that Christian Eriksen is recovering following his collapse during Denmark s match against Finland and send him their best wishes	2021-06-13 12:34:27
北海道	北海道新聞	ＦＣ東京、札幌、浦和が８強　ルヴァン杯ＰＯ第２戦	https://www.hokkaido-np.co.jp/article/555076/	浦和	2021-06-13 21:03:00
北海道	北海道新聞	ファミレスに車突っ込む　６６歳女性、歩行者はね	https://www.hokkaido-np.co.jp/article/555067/	静岡県沼津市大岡	2021-06-13 21:02:16