投稿時間:2022-01-04 07:20:07 RSSフィード2022-01-04 07:00 分まとめ(24件)

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IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] ユニクロもついに値上げか？　食品メーカーが次々決断する中、アパレルだけが踏み切れない“不自然”な理由	https://www.itmedia.co.jp/business/articles/2201/04/news002.html	itmedia	2022-01-04 06:30:00
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] ファミマが掲げる“無人1000店”　小型・無人化で開拓する新たな商圏とは？	https://www.itmedia.co.jp/business/articles/2201/04/news006.html	itmedia	2022-01-04 06:30:00
AWS	AWS Security Blog	How to configure an incoming email security gateway with Amazon WorkMail	https://aws.amazon.com/blogs/security/how-to-configure-an-incoming-email-security-gateway-with-amazon-workmail/	How to configure an incoming email security gateway with Amazon WorkMailThis blog post will walk you through the steps needed to integrate Amazon WorkMail with an email security gateway Configuring WorkMail this way can provide a versatile defense strategy for inbound email threats Amazon WorkMail is a secure managed business email and calendar service WorkMail leverages the email receiving capabilities of Amazon Simple Email Service …	2022-01-03 21:37:21
AWS	AWS Security Blog	How to configure an incoming email security gateway with Amazon WorkMail	https://aws.amazon.com/blogs/security/how-to-configure-an-incoming-email-security-gateway-with-amazon-workmail/	How to configure an incoming email security gateway with Amazon WorkMailThis blog post will walk you through the steps needed to integrate Amazon WorkMail with an email security gateway Configuring WorkMail this way can provide a versatile defense strategy for inbound email threats Amazon WorkMail is a secure managed business email and calendar service WorkMail leverages the email receiving capabilities of Amazon Simple Email Service …	2022-01-03 21:37:21
Ruby	Rubyタグが付けられた新着投稿 - Qiita	【Rails 6】1つのコントローラー、ビューで複数モデルに対応した汎用性高めのCSVインポート機能を作る	https://qiita.com/kazama1209/items/134bdd59e7aabbc7dd2f	主な内容つのコントローラー、ビューで複数モデルのCSVインポートに対応データ挿入前にプレビュー画面を挟み、取り込み予定データの内容を確認可能CSVファイルの中身に問題があった場合、何行目のどこが悪いかを表示全体的にDryかつコンパクトに、たとえ後に対象のモデルが増えたとしてもなるべく少量の追記で対応できるように心がけました。	2022-01-04 06:09:55
Azure	Azureタグが付けられた新着投稿 - Qiita	Azure CosmosDBとFIWARE Orionを連携させる	https://qiita.com/nmatsui/items/7f81e8119c2968941348	この時点ではFIWAREOrionで検証したのですが、AzureCosmosDBのMongoDBAPIではOrionを動作させることができませんでした。	2022-01-04 06:59:59
Git	Gitタグが付けられた新着投稿 - Qiita	GitHubにpushしても芝生が生えないとき、過去に遡って草を再生する魔法	https://qiita.com/HIJIKI/items/9b2d1b8b5f0fea1e7883		2022-01-04 06:08:15
Ruby	Railsタグが付けられた新着投稿 - Qiita	【Rails 6】1つのコントローラー、ビューで複数モデルに対応した汎用性高めのCSVインポート機能を作る	https://qiita.com/kazama1209/items/134bdd59e7aabbc7dd2f	主な内容つのコントローラー、ビューで複数モデルのCSVインポートに対応データ挿入前にプレビュー画面を挟み、取り込み予定データの内容を確認可能CSVファイルの中身に問題があった場合、何行目のどこが悪いかを表示全体的にDryかつコンパクトに、たとえ後に対象のモデルが増えたとしてもなるべく少量の追記で対応できるように心がけました。	2022-01-04 06:09:55
海外TECH	Ars Technica	Exchange Server bug gets a fix after ruining admin’s New Year’s plans	https://arstechnica.com/?p=1823272	couldn	2022-01-03 21:47:39
海外TECH	Ars Technica	Reminder: Donate to win swag in our annual Charity Drive sweepstakes [Updated]	https://arstechnica.com/?p=1823274	charity	2022-01-03 21:27:25
海外TECH	MakeUseOf	What Does Audio Grade Mean & How Do Regular Components Differ?	https://www.makeuseof.com/what-does-audio-grade-mean/	What Does Audio Grade Mean amp How Do Regular Components Differ Do audio grade speaker components make speakers better What makes these components audio grade in the first place and are they even worth the money	2022-01-03 22:00:12
海外TECH	DEV Community	What was your greatest "aha" moment as a JavaScript developer?	https://dev.to/sherrydays/what-was-your-greatest-aha-moment-as-a-developer-1cpj	javascript	2022-01-03 21:37:42
海外TECH	DEV Community	10 Github Extensions for VS Code that will ease your work 😀	https://dev.to/yokwejuste/10-github-extensions-for-vs-code-that-will-ease-your-work-121c	Github Extensions for VS Code that will ease your work Hello World Let s dive into something concerning open source today once more When mentioning open source the term VCS Version Control system deserves a great focus What is Github all about This is just one of the numerous version control systems we do have but what does that mean When developers create something an app website for example they make updates to the code releasing new versions up to after the first one and so on As a whole a VCS is Version control systems keep these revisions straight storing the modifications in a central repository This allows developers to easily collaborate as they can download a new version of the software make changes and upload the newest revision Every developer can see these new changes download them and contribute VS Code extensions for Github Introduction In general VS Code extensions let you add languages debuggers and tools to your installation to support your development workflow and much more The Extensions GitLive   ️K This sweet extension is actually for you who like teamwork and open source With GitLive you can see your fellow partners online and be aware of which part of your project they re working on currently By so doing too you limit you resolve conflicts before they happen by checking their local files Git Graph  ️M Git Graph is the best visual way one can interact with Git in VS Code having a look at the git tree where he can perform simple to very complex actions This extension offers high customizability depending on the user preference over the tree You can click on any commit to view details and file changes and you can even perform code reviews without leaving your IDE Git Urgent  ️K This one I put in the category of simple but effective With this extension installed all you have to do is search “Git Urgent in the VS Code command palette and you can git add all commit and push with one command Git Automator  ️K When in the haste and being lazy nothing better than the git automaton it helps us skip from all the usual commands we use to type when we want to make a commit a fetch or even a pull Git Automator allows you to add and commit files with a shortcut It also provides auto prefills for commit messages When the action is obvious for example if you have deleted a file Git Automator will guess the action and add it to the prefilled commit message Git Tree Compare   ️K Working tree comparison against any chosen branch tag or commit and keeps you on track by giving you an overview of how your pull request will look like After choosing the base for the comparison you can either choose to open All Changes or open Changed Files files that were added will be opened as well but changes won t be shown You can also choose whether to compare against the selected base ref directly full mode or by computing a merge base first merge mode GitLens   ️M GitLens is powerful feature rich and highly customizable to meet your needs This is one of the best and highly downloaded VS Code extensions for git With over Million downloads GitLens helps you to jump back through history to gain further insights as to how and why the code evolved On the hoover of the code the last commit message is shown together with the commit date Git History   ️M Among all this is one of the prettiest and useful extensions for git It keeps different versions of files under the git repository from initial commit to final or last commit Also gives you the ability to have different versions of the file compare branches GitHub Pull Requests and Issues   ️M Special extension built by the Github team and it aVS Code text editor to your GithubAuthenticating and connecting VS Code to GitHub GitHub Enterprise is supported by the community please see this PR for how to set it up Makes all your pull requests issues branches helps you to check and validate them GitHub Copilot   ️K GitHub Copilot is an artificial intelligence tool developed by GitHub and OpenAI to assist users of Visual Studio Code Neovim and JetBrains by autocompleting block code Nothing is best than choosing Github Copilot as your coding assistant It possesses regular expressions by developers on Github GitHub Codespaces   ️K It provides cloud hosted development environments for any activity whether it s a long term project or a short term task like reviewing a pull request You can connect to Codespaces from Visual Studio Code or a browser based editor that s accessible anywhere ConclusionRead and get your own interesting extension surely you felt in love with one or another	2022-01-03 21:33:10
海外TECH	DEV Community	Asteria: Asteroids approaching Earth today	https://dev.to/valeriavg/asteria-asteroids-approaching-earth-today-1o23	Asteria Asteroids approaching Earth today OverviewThis project shows a list of asteroids and other objects that are approaching Earth today Worry not though most of them will miss our planet by dozens of millions of kilometers See live Submission Category Choose Your Own Adventure Link to Code ValeriaVG asteria Asteroids approaching Earth today How it worksRealm function fetchNEOFeed uses NASA API to fetch a list of approaching near Earth objects transforms them to a more appropriate form and upserts them to a MongoDB collection Scheduled Realm trigger runs this function every hour Filled collection is used to generate Realm GraphQL schema Realm Hosting hosts minimalistic web page that fetches data from GraphQL server and renders it Hope you like it And let s hope we shall never see this	2022-01-03 21:19:09
海外TECH	DEV Community	A run-through on Random Forest in Machine learning	https://dev.to/simi/a-run-through-on-random-forest-in-machine-learning-457	A run through on Random Forest in Machine learningData scientists employ a wide range of algorithms to receive and analyze input data to predict output values within an acceptable range The more experience a data scientist gains the more they know the right algorithm to use for each problem Random Forest is one of the extremely useful algorithm since it works for both classification and regression tasks In this article you ll learn all you need to know about Random Forest We ll cover What is Random Forest What Random Forest is used for How Random Forest works Important Hyper parametersHow execute Random Forest with lines of codeAdvantages of Random ForestDisadvantages of Random Forest What is Random Forest Random Forests also known as random decision forests are ensemble learning method for classification regression and other tasks that works by constructing a multitude of decision trees at training time For classification tasks the output of the Random Forest is the class selected by most trees Random Forest is also a supervised machine learning algorithm that grows and combines decision trees to make a forest Random Forest can be used for both classification and regression tasks in R and python Before we explore more details in Random Forest let s break down the keywords in the definition Supervised machine learningClassification and regressionDecision treeUnderstanding these keywords will make you understand the concept of Random Forest we initiate with Supervised machine learning is a category of machine learning and artificial intelligence that uses labeled datasets to train algorithms to classify data or predict outcomes accurately A good example of supervised learning problems is predicting house prices First we need data about the houses square footage number of rooms features whether a house has a swimming pool or not and so on We then need to know the prices of these houses i e the corresponding labels Using the data coming from thousands of houses their features and prices we can now train a supervised machine learning model to predict a new house s price based on the examples observed by the model Classification and RegressionClassification is the process of finding a model that helps in the separation of data into multiple categorical classes discrete values Regression is the process of finding a model that distinguishes the data into continuous real values rather than classes or discrete values A simpler way to distinguish both remember that classification uses discrete values yes or no or etc while regression uses continuous values Decision TreeAs said earlier on Random Forest model combines multiple decision trees to make a forest A decision tree is a decision support tool that uses a tree like model of decisions and their possible consequences including chance event outcomes resources cost and so on A decision tree consists of three components decision nodes leaf nodes and a root node Decision node has two or more branches e g sunny windy and rainy Leaf node represents a classification or decision Root node the topmost decision node that corresponds to the best predictor A decision tree algorithm divides a training dataset into branches which further segregate into other branches This sequence continues until a leaf node is attained The leaf node cannot be segregated further What Random Forest is used for Random Forest is used by Data scientist on jobs in many industries like banking medicine e commerce and so on Random Forest is used to predict things that would help these industries run efficiently In banking to predict customers who are more likely to repay their debts also those who will use the bank s services more frequently In health care Random Forest can be used to analyze a patient s medical history to identify the sickness Also in the study of genetics Retail companies also use Random Forest to recommend products and predict customer satisfaction as well How Random Forest worksBefore we look into how Random Forest works we need to look into the ensemble technique as used in the definition of Random Forest Ensemble means combining multiple models Thus a collection of models is used to make predictions rather than an individual model Ensemble uses two types of methods Bagging It creates a different training subset from sample training data with replacement amp the final output is based on majority voting For example Random Forest Decision trees in an ensemble like the trees within Random Forest are usually trained using the bagging method The bagging method is also a type of ensemble machine learning algorithm called Bootstrap Aggregation Bootstrap randomly performs row sampling and feature sampling from the dataset to form sample datasets for every model  Aggregation reduces these sample datasets into summary statistics based on the observation and combines them Bootstrap Aggregation can be used to reduce the variance of high variance algorithms such as decision trees Boosting It combines weak learners into strong learners by creating sequential models such that the final model has the highest accuracy For example ADA BOOST XG BOOST An ensemble method combines predictions from multiple machine learning algorithms together to make more accurate predictions than an individual model Random Forest is also an ensemble method VarianceVariance is an error resulting from sensitivity to small fluctuations in the dataset used for training High variance will cause an algorithm to model irrelevant data or noise in the dataset instead of the intended outputs called signal This problem is called overfitting An overfitted model will perform well in training but won t be able to distinguish the noise from the signal in an actual test Steps involved in random forest algorithm Step I In Random Forest number of random records n are taken from the data set with a number of records k Step II Individual decision trees are constructed for each sample Step III Each decision tree will generate an output Step IV Final output is considered based on Majority Voting or Averaging  for Classification and regression respectively Consider the fruit basket as the data as shown in the figure above Now n number of samples are taken from the fruit basket and an individual decision tree is constructed for each sample Each decision tree will generate an output as shown in the figure The final output is considered based on majority voting In the figure above you can see that the majority decision tree gives output as an apple when compared to a banana so the final output is taken as an apple Important HyperparametersThe hyperparameters in Random Forest are either used to increase the predictive power of the model or to make the model faster Let s look at these hyperparameters To increase the predictive power n estimators This is the number of trees the algorithm builds before taking the maximum voting or taking the averages of predictions In general a higher number of trees increases the performance and makes the predictions more stable but it also slows down the computation max features This is the maximum number of features random forest considers to split a node min sample leaf This determines the minimum number of leafs required to split an internal node max depth This specifies the maximum dept of each tree The default value for max depth is None which means that each tree will expand till every leaf is pure all of the data come from the same class There has been some work that says best depth is  splits It of course depends on the problem and data To increase the model s speed n jobs This hyperparameter tells the engine how many processors it is allowed to use If it has a value of one it can only use one processor A value of “ means that there is no limit random state This hyperparameter makes the model s output replicable The model will always produce the same results when it has a definite value of random state and if it has been given the same hyperparameters and the same training data oob score Also known as oob sampling It is a random forest cross validation method In this sampling about one third of the data is not used to train the model and can be used to evaluate its performance These samples are called the out of bag samples It s very similar to the leave one out cross validation method How to execute Random Forest with lines of codeNow let s understand how to implement Random Forest with lines of code import necessary libraries e g pandas matplotlib and so on import dataset clean the dataset if necessary visualize if necessary spilt the dataset into train and test import Random Forest model classifierfrom sklearn ensemble import RandomForestClassifierclf RandomForestClassifier n estimators random state fit the model using the training setsclf fit X train y train check predictionsy pred clf predict X test check accuracy with the actual and predicted values import sci kit learn metrics module to check accuracyfrom sklearn import metricsmetrics accuracy score y test y pred regressorfrom sklearn ensemble import RandomForestRegressorreg RandomForestRegressor n estimators random state train the model using the training setsreg fit X train y train check predictionsy pred reg predict X test check accuracy with the actual and predicted values import sci kit learn metrics module to check accuracyfrom sklearn import metricsmetrics accuracy score y test y pred Advantages of Random ForestRandom Forest is more efficient than a single decision tree when performing analysis on a very large databases Also Random Forest produces a great result without hyperparameter tuning The following are advantages of using Random Forest It reduces overfitting in decision trees and helps to improve the accuracy It is flexible to both classification and regression problems It works well with both categorical and continuous values It automates missing values present in the data Normalising of data is not required as it uses a rule based approach It takes less time and expertise to develop Random Forest is really useful talk about the avengers of algorithms Disadvantages of Random ForestLike every other thing Random Forest also has some draw backs It requires much time for training as it combines a lot of decision trees to determine the class Due to the ensemble of decision trees it also suffers interpretability and fails to determine the significance of each variable It requires much computational power as well as resources as it builds numerous trees to combine their outputs It is a predictive modeling tool and not a descriptive tool meaning if you re looking for a description of the relationships in your data other approaches would be better Test your knowledge Which of the following is are true about Random Forest I It can be used for classification task s II It can be used for regression task s III It is the act or process of classifyingIV NoneA I amp IIB I onlyC II onlyD IVRandom Forest is a supervised or unsupervised learning model A Supervised learningB Unsupervised learningC NoneD BothWhen does overfitting occur A The model performs well on testing and not so well on training B The model performs well on both the testing and training C The model doesn t perform well on both testing and training D The model performs well on the training but not on the testing The bagging method is a type of ensemble machine learning algorithms called A Bagging B Bootstrap C Aggregation D Bootstrap Aggregation Thanks for reading Keep scrutinizing	2022-01-03 21:17:51
海外TECH	DEV Community	Is Matrix ready to compete in today's messenger apps?	https://dev.to/archerallstars/is-matrix-ready-to-compete-in-todays-messenger-apps-2plp	Is Matrix ready to compete in today x s messenger apps What is Matrix In order to get an understanding of what Matrix really is it s the best to check it out directly from the official documentation However to put it in layman s terms Matrix lets you choose the public server that you want to use it on It even allows you to host and use it on your server So you won t be locked to a specific server And you can also communicate with your friends who are on different Matrix servers or different Matrix clients altogether In fact you can even communicate with friends who are using other messenger apps via Bridges Other messenger apps on the other hand won t let you choose the server provider you want to use their services on For example if you use WhatsApp you have no option to choose the server channel And you can t communicate with your friends who use Telegram or any other messenger apps from within WhatsApp The same goes for LINE Telegram Discord Signal and etc What is the problem with other messenger apps The problem lies within the nature of their services Since most if not all of the well known messenger apps are centralized the providers have full control on how they provide their services Let s see how some of them manages the privacy of your messages WhatsApp is pretty safe as they enable end to end encryption by default And according to their privacy policy they do not store our messages on their server However since the client is not open source we have no way to know what s really happening there Facebook Messenger is not as safe as the others since they don t enable end to end encryption by default However they re trying very hard to make it happen sometime in at the earliest This means currently most of the people s messages on their service are exposing for everyone to see But at least they promised you to not use your messages for ad targeting LINE is a very popular messenger app among Asians It has end to end encryption which they called Letter Sealing enabled by default It s not clear what encryption technology they re using However according to their privacy policy it seems they can see use our messages in a private chat room if such use is permitted under Applicable Laws Discord according to their privacy policy they openly say that they will collect your data It s needless to say that data encryption or anything of the sort can t be found in their privacy policy And you wouldn t believe how many business entities use Discord as their internal communication IMO out of all communication apps Discord is the most feature rich Therefore it s not beyond believing why many businesses use it thus not be limited to only gamers Telegram according to their privacy policy they enable end to end encryption only in your Secret Chats The downside of using Secret Chats is that it won t sync across your devices However the normal chat room that many users are familiar with is called Cloud Chats of which your messages along with other data will be stored at Telegram s servers But this doesn t mean their local engineers will be able to read your messages in their free time Your data will be heavily encrypted and the keys to unlock that will be stored at different places Nevertheless their client is open source so you can check whether their apps hide something away from you Signal enable end to end encryption by default Their client is open source of which you can grab the code and even run it on your own server Nevertheless you still need a phone number in order to use their services If you want to use Signal without a phone number you will have to use it on your self hosting Signal server But that would mean you won t be able to talk to your friends on the official Signal server since they re on the different server than you hence the centralized nature of the services Welcome to the decentralized messenger party As you can see all the popular messenger communication apps from above have one thing in common they re locking down users in their platform The users have no choice to opt out from them contrary to Matrix which allow the user to choose the client and the server they want to use Therefore the users can talk to each other regardless of what client and sever they re using Choosing the ServerSince Matrix is not currently a PP communication protocol they re working on it you will have to use it through a server which is known as homeserver And the homeserver that people use the most is of course the official Matrix org server Therefore we better checkout the server s privacy notice also According to their privacy notice they make it pretty clear that they can t see your messages in encrypted rooms of which use end to end encryption to encrypt your messages And the keys to unlock your encrypted messages are stored only on your devices or by yourself which is as safe as it can be Moreover both email address and phone number are totally optional as shown in my profile screenshot below However if you want to opt out from the official server the most recent list of the unofficial Matrix servers can be found here Or if you want to run your self hosting Matrix server you can get start by this installing Synapse guide Choosing the ClientMost people use Element as their Matrix client Since Element was founded by the team behind Matrix it s kind of the official client for Matrix that people expected it to be the most matured and feature rich Element is an open source Matrix client which you can grab the code on their GitHub repositories Currently they have US and US monthly subscription plans available for end users which will give you some more connection speed and some more bridges to connect to your friends on other messenger apps from within Element Moreover they also have subscription plans for enterprise users and their Matrix hosting services as well Or if you want to support The Matrix org Foundation directly you can go to their Patreon page or buy some T Shirts at their shop here However if you don t want to use Element as your Matrix client you can find a full list of Matrix clients here What is still preventing us from using Matrix as our main messenger app It s not only about the robust technology that will workout for the platform network Otherwise for instance Google with that kind of technology plus money and marketing power wouldn t fail According to Statista s report in billion users were accessing the WhatsApp messenger on a monthly basis And according to Element s website around millions users are connecting to Matrix That s around when compared to WhatsApp It seems like Matrix s position in the messenger apps market is very similar to Linux s position in the desktop PC market So why didn t people use it considered all the benefits as explained above No friend here Of course the reason we use our communication at all is to communicate with other people especially friends and family members If the people we care are not on this network it s pointless Matrix s Bridges can help with this issue to some extent However it s not a viable option for average users The accessible Bridges in free tier Element are IRC and Slack that most people have never heard of Even though the users can pay the subscription plans to access more Bridges but that would diminish the point of using Matrix I see Bridges more like a relief not a solution Nevertheless to change how people do their things is not an easy task They re most likely to continue using centralized messenger apps just because they re familiar with them without caring much about privacy issues I am very sure that most people would choose to have cute stickers in their collection before having their privacy back any day of the week This is Matrix s homework to sort it out together with many Matrix client developers Unmatured Client yet Matrix itself introduced version in let alone Element If you expected Element to be extremely stable you could be wrong In my experience for using Element on Android for a while I can say that it s far from stable and complete I as an advocate successfully got some of my friends and family members to use Element At first they were very interested about it However they re now quitted as there s no option to start a group voice call They went back to LINE and don t look back on Element again due to the lack of this very basic feature Here s my bug report regarding this issue I also successfully got my team in a project that I m working on to switch from Discord to Element They re not happy about it as the screen sharing feature that s supposed to work doesn t work at all Currently the group video call in Element is handled by Jitsi Basically you re using Jitsi Meet inside Element but without screen sharing Regarding these issues the team has already made it as the roadmap to address among all the others in their roadmap Moreover there s still a lot of UI UX issues that need be fixed or refined You can search and help reporting and debugging the issues at the official issues tracker here ConclusionMatrix is a great technology in the communication space I have no doubt about that However there s so many things that need to be done before it can compete with other players in the market Or to put it more precisely that s the work for every Matrix client developers and servers to penetrate this market together I hope this is a good read for you all Cover photo by Quino Al on UnsplashBrown Sheep photo by Jo Anne McArthur on UnsplashAn Unlocked Locker photo by Basil James on UnsplashA Person Behind a Fog Glass photo by Stefano Pollio on UnsplashA Man Smoking photo by Akshay Bora on Unsplash	2022-01-03 21:16:40
Apple	AppleInsider - Frontpage News	Oral-B debuts three new iPhone-connected iO smart toothbrushes	https://appleinsider.com/articles/22/01/03/oral-b-debuts-three-new-iphone-connected-io-smart-toothbrushes?utm_medium=rss	Oral B debuts three new iPhone connected iO smart toothbrushesAt the Consumer Electronics Show Oral B debuted three new smart toothbrushes dedicated to helping users improve the health of their teeth and gums with real time feedback and on device pressure control ーand brought back the Cavity Creeps Oral B initially launched the iO line in to help users achieve superior at home cleaning Oral B iO brushes achieve this through D brushing recognition pressure control and a built in brushing timer According to Oral B iO users involved in a clinical trial experienced Read more	2022-01-03 21:44:27
Apple	AppleInsider - Frontpage News	Apple promotes Fitness+ and Apple Watch with new homepage takeover	https://appleinsider.com/articles/22/01/03/apple-promotes-fitness-and-apple-watch-with-new-homepage-takeover?utm_medium=rss	Apple promotes Fitness and Apple Watch with new homepage takeoverApple is promoting its Apple Fitness workout service in the new year with a homepage takeover and the company is also continuing to offer three months of service to new Apple Watch buyers Apple Fitness homepage takeoverUsers who visit Apple com will see a promotional video showing off the Apple Fitness service including various workouts taught by the company s trainers After the clip plays Apple encourages users to Learn more about Fitness Read more	2022-01-03 21:39:09
ニュース	BBC News - Home	South Africa parliament fire flares up again	https://www.bbc.co.uk/news/world-africa-59861556?at_medium=RSS&at_campaign=KARANGA	flares	2022-01-03 21:06:12
ビジネス	ダイヤモンド・オンライン - 新着記事	米コロナ新規感染、過去最多の40万人超 - WSJ発	https://diamond.jp/articles/-/292361	過去最多	2022-01-04 06:20:00
ビジネス	東洋経済オンライン	｢軽自動車のEV化｣がいまいちピンとこない理由 新型アルトに乗って案じた｢軽EVの行方｣ | 軽自動車 | 東洋経済オンライン	https://toyokeizai.net/articles/-/479752?utm_source=rss&utm_medium=http&utm_campaign=link_back	東洋経済オンライン	2022-01-04 06:30:00
マーケティング	MarkeZine	「自立」と「挑戦」ができる環境を作る。サイボウズ大槻氏に聞く、チームビルディング	http://markezine.jp/article/detail/38023	「自立」と「挑戦」ができる環境を作る。	2022-01-04 06:30:00
海外TECH	reddit	OU QB Caleb Williams has entered the transfer portal	https://www.reddit.com/r/CFB/comments/rvc2mk/ou_qb_caleb_williams_has_entered_the_transfer/	OU QB Caleb Williams has entered the transfer portal s submitted by u Notre Dame Football to r CFB link comments	2022-01-03 21:07:47
ニュース	THE BRIDGE	AI搭載心電計開発Huinnoが上場目前に42億円調達など——韓国スタートアップシーン週間振り返り（12月27日~12月31日）	https://thebridge.jp/2022/01/startup-recipe-dec-27-dec-31	AI搭載心電計開発Huinnoが上場目前に億円調達などー韓国スタートアップシーン週間振り返り月日月日本稿は、韓国のスタートアップメディア「StartupRecipe스타트업레시피」の発表する週刊ニュースを元に、韓国のスタートアップシーンの動向や資金調達のトレンドを振り返ります。	2022-01-03 21:00:47