投稿時間:2023-04-17 16:29:19 RSSフィード2023-04-17 16:00 分まとめ(33件)

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IT	InfoQ	.NET MAUI 8 Preview 3: UI improvements, Memory Management, and NuGet Versioning	https://www.infoq.com/news/2023/04/dotnet-maui-8-preview-3/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global	NET MAUI Preview UI improvements Memory Management and NuGet VersioningMicrosoft has recently released the third preview of the NET MAUI framework in NET This latest release includes UI improvements focusing on memory management also In addition Preview also brings support for NuGet package versions of the app This means that developers will now have the ability to preview future builds and lock their applications to a specific version of NET MAUI By Almir Vuk	2023-04-17 06:30:00
ROBOT	ロボスタ	眼内内視鏡・眼内照明保持ロボット「OQrimo」(オクリモ)を製品化　九州大学/東京工業大学/順天堂大学/山口大学/リバーフィールドが共同開発	https://robotstart.info/2023/04/17/oqrimo.html	眼内内視鏡・眼内照明保持ロボット「OQrimo」オクリモを製品化九州大学東京工業大学順天堂大学山口大学リバーフィールドが共同開発シェアツイートはてブ九州大学、東京工業大学、順天堂大学、山口大学およびリバーフィールドは、共同開発した眼内内視鏡・眼内照明保持ロボット「OQrimoオクリモ」の製品化に成功したことを発表した。	2023-04-17 06:13:03
IT	ITmedia 総合記事一覧	[ITmedia News] Amazon、22日から「GW SALE」開催へ　「AirPods」などもセール対象に	https://www.itmedia.co.jp/news/articles/2304/17/news123.html	airpods	2023-04-17 15:30:00
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] ゴーゴーカレー、サッカー本田圭佑氏が主要株主に　狙いは？	https://www.itmedia.co.jp/business/articles/2304/17/news118.html	itmedia	2023-04-17 15:30:00
IT	ITmedia 総合記事一覧	[ITmedia News] ChatGPTで育児をちょっとラクにする	https://www.itmedia.co.jp/news/articles/2304/17/news122.html	itmedianewschatgpt	2023-04-17 15:23:00
IT	ITmedia 総合記事一覧	[ITmedia News] ペルチェ素子とファン搭載の「冷蔵服2」、サンコーが発売	https://www.itmedia.co.jp/news/articles/2304/17/news121.html	itmedia	2023-04-17 15:22:00
IT	ITmedia 総合記事一覧	[ITmedia エンタープライズ] SAP、オラクル、ワークデイはSaaS革命を起こすか　クラウドERP「三大勢力」の動向から考察	https://www.itmedia.co.jp/enterprise/articles/2304/17/news110.html	itmedia	2023-04-17 15:20:00
IT	ITmedia 総合記事一覧	[ITmedia News] 楽天ペイの請求書払い始まる　ポイントで税金も支払い可能　ただし上限金額は30万円	https://www.itmedia.co.jp/news/articles/2304/17/news104.html	itmedia	2023-04-17 15:10:00
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] 三重県伊勢市に「グランピング施設」オープン、特徴は？	https://www.itmedia.co.jp/business/articles/2304/17/news105.html	itmedia	2023-04-17 15:07:00
TECH	TechAcademyマガジン	転職・在宅ワークにも繋がる！Web制作の副業の仕事内容と収入を徹底解説	https://magazine.techacademy.jp/magazine/83959	転職・在宅ワークにも繋がるWeb制作の副業の仕事内容と収入を徹底解説皆さんは本業の収入やお仕事に満足していますか「転職するほど不満があるわけではないけど将来を考えた時にこのままで良いか、なんとなく不安」という方が多いのではないでしょうか。	2023-04-17 06:25:22
IT	情報システムリーダーのためのIT情報専門サイト IT Leaders	スマートスタイル、MySQL HeatWaveのPoC支援SIを提供、費用対効果を技術的観点から検証 | IT Leaders	https://it.impress.co.jp/articles/-/24735	スマートスタイル、MySQLHeatWaveのPoC支援SIを提供、費用対効果を技術的観点から検証ITLeadersMySQLなどオープンソースソフトウェアのSIベンダーであるスマートスタイルは年月日、SIサービス「MySQLHeatWavePoCサービス」を提供開始した。	2023-04-17 15:31:00
AWS	AWS Japan Blog	大規模モデル推論コンテナを使って AWS Inferentia2 に大規模言語モデルをデプロイ	https://aws.amazon.com/jp/blogs/news/deploy-large-language-models-on-aws-inferentia2-using-large-model-inference-containers/	大規模モデル推論コンテナを使ってAWSInferentiaに大規模言語モデルをデプロイ本稿では、AWSInferentia上で大規模言語モデルをデプロイする方法を解説します。	2023-04-17 06:28:53
AWS	AWS Japan Blog	低コストで高性能な生成系 AI 推論用の Amazon EC2 Inf2 インスタンスが一般公開されました	https://aws.amazon.com/jp/blogs/news/amazon-ec2-inf2-instances-for-low-cost-high-performance-generative-ai-inference-are-now-generally-available/	amazonecinf	2023-04-17 06:07:07
python	Pythonタグが付けられた新着投稿 - Qiita	[無料枠] ngrokをPythonでデーモン化しアドレスをメール通知する	https://qiita.com/yukimasaki/items/72cb1c920261dfbe3fb9	ngrok	2023-04-17 15:58:33
Ruby	Rubyタグが付けられた新着投稿 - Qiita	Windows10環境へRedmineをインストール	https://qiita.com/RottenOrange/items/93b08858b0e6ccb325cb	redmine	2023-04-17 15:42:51
技術ブログ	Developers.IO	【登壇資料】組織的なクラウド統制のはじめの一歩〜AWSのクラウド統制サービスの紹介〜	https://dev.classmethod.jp/articles/230405-ccoe-webinar-session-1-2/	資料	2023-04-17 06:27:19
技術ブログ	Developers.IO	VPC Lattice クロスアカウント接続に必要な要素を図解してみた	https://dev.classmethod.jp/articles/illustrates-vpc-lattice-cross-account-connectivity/	vpclattice	2023-04-17 06:10:12
海外TECH	DEV Community	Dynamic Programming Algorithms Every Programmer Should Know	https://dev.to/rishitashaw/dynamic-programming-algorithms-every-programmer-should-know-3915	Dynamic Programming Algorithms Every Programmer Should KnowDynamic programming is a popular technique in computer science and software engineering that plays a crucial role in competitive programming It is a method for solving complex problems by breaking them down into smaller subproblems and solving each subproblem only once storing the solutions to subproblems so that they can be reused when needed In this blog we will explore the necessary Dynamic Programming algorithms that every competitive programmer should know Fibonacci NumbersThe Fibonacci sequence is a well known series of numbers that are defined by the recurrence relation F n F n F n with the base case F and F A simple recursive algorithm for calculating Fibonacci numbers would be to use the recurrence relation directly but this would lead to exponential time complexity Dynamic programming allows us to solve this problem in linear time by using memoization which is storing the results of already solved subproblems def fibonacci n memo if n in memo return memo n if n lt memo n n else memo n fibonacci n memo fibonacci n memo return memo n Longest Common SubsequenceThe Longest Common Subsequence LCS problem is a classic dynamic programming problem that involves finding the longest subsequence that is common to two given strings A subsequence of a string is a sequence of characters that appears in the same order in the string but not necessarily consecutively The LCS problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def lcs s s m n len s len s dp n for in range m for i in range m for j in range n if s i s j dp i j dp i j else dp i j max dp i j dp i j return dp m n Knapsack ProblemThe Knapsack problem is a classic optimization problem that involves finding the optimal subset of items to pack into a knapsack with a finite capacity so as to maximize the value of the items packed This problem can also be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def knapsack W wt val n dp W for in range n for i in range n for w in range W if wt i lt w dp i w max val i dp i w wt i dp i w else dp i w dp i w return dp n W Edit DistanceThe Edit Distance problem involves finding the minimum number of operations required to transform one string into another The operations allowed are insertion deletion and substitution This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def edit distance s s m n len s len s dp n for in range m for i in range m for j in range n if i dp i j j elif j dp i j i elif s i s j dp i j dp i j else dp i j min dp i j dp i j dp i j return dp m n Maximum SubarrayThe Maximum Subarray problem involves finding the contiguous subarray within a one dimensional array of numbers that has the largest sum This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def max subarray arr n len arr max sum float inf current sum for i in range n current sum arr i max sum max max sum current sum current sum max current sum return max sum Coin ChangeThe Coin Change problem involves finding the number of ways to make change for a given amount of money using a given set of coin denominations This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def coin change coins amount dp float inf amount dp for i in range amount for coin in coins if coin lt i dp i min dp i dp i coin return dp amount if dp amount float inf else Matrix Chain MultiplicationThe Matrix Chain Multiplication problem involves finding the optimal way to multiply a series of matrices together This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once It is a classic example of dynamic programming and is used in many fields such as computer graphics numerical analysis and scientific computing def matrix chain order p n len p m float inf n for in range n s n for in range n for i in range n m i i for l in range n for i in range n l j i l for k in range i j q m i k m k j p i p k p j if q lt m i j m i j q s i j k return m s Longest Increasing SubsequenceThe Longest Increasing Subsequence LIS problem involves finding the longest subsequence of a given sequence that is strictly increasing This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once The LIS problem has many real world applications such as in data compression pattern recognition and bioinformatics def lis arr n len arr dp n for i in range n for j in range i if arr i gt arr j dp i max dp i dp j return max dp Traveling Salesman ProblemThe Traveling Salesman Problem TSP involves finding the shortest possible route that visits a given set of cities and returns to the starting city This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once The TSP is a classic problem in computer science and has many real world applications such as in logistics transportation and network optimization def tsp graph start n len graph visited lt lt n memo def dfs node visited if visited return graph node start if node visited in memo return memo node visited ans float inf for i in range n if visited amp lt lt i ans min ans graph node i dfs i visited lt lt i memo node visited ans return ans return dfs start visited Integer ProgrammingThe Integer Programming problem involves finding the optimal solution for a set of binary decision variables subject to a set of constraints This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once The Integer Programming problem has many real world applications such as in resource allocation scheduling and production planning def knapsack W wt val n dp W for in range n for i in range n for w in range W if wt i lt w dp i w max val i dp i w wt i dp i w else dp i w dp i w return dp n W Edit Distance with Allowed OperationsThe Edit Distance problem can be extended to allow only a certain set of edit operations such as insertion deletion and substitution This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def edit distance with allowed ops s s allowed ops m n len s len s dp n for in range m for i in range m dp i i for j in range n dp j j for i in range m for j in range n if s i s j dp i j dp i j elif allowed ops get s i s j op cost allowed ops s i s j dp i j min dp i j op cost dp i j op cost dp i j op cost else dp i j min dp i j dp i j dp i j return dp m n Longest Palindromic SubstringThe Longest Palindromic Substring problem involves finding the longest substring of a given string that is a palindrome This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def longest palindromic substring s n len s dp False n for in range n max len start for i in range n dp i i True for l in range n for i in range n l j i l if l dp i j s i s j else dp i j s i s j and dp i j if dp i j and l gt max len max len l start i return s start start max len Maximum Product SubarrayThe Maximum Product Subarray problem involves finding the contiguous subarray within a one dimensional array of numbers that has the largest product This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def max product subarray nums n len nums max prod nums min prod nums max so far nums for i in range n temp max prod max prod max nums i max nums i max prod nums i min prod min prod min nums i min nums i temp nums i min prod max so far max max so far max prod return max so far Largest Rectangle in a HistogramThe Largest Rectangle in a Histogram problem involves finding the largest rectangle that can be formed in a histogram composed of rectangles with different heights This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def largest rectangle area heights n len heights left n right n stack for i in range n while stack and heights stack gt heights i stack pop left i stack if stack else stack append i stack for i in range n while stack and heights stack gt heights i stack pop right i stack if stack else n stack append i max area for i in range n max area max max area heights i right i left i return max area Egg Dropping ProblemThe Egg Dropping Problem involves finding the minimum number of attempts required to find out the highest floor from which an egg can be dropped without breaking This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def egg drop n k dp k for in range n for i in range n dp i dp i for j in range k dp j j for i in range n for j in range k dp i j float inf for x in range j res max dp i x dp i j x dp i j min dp i j res return dp n k Counting BitsThe Counting Bits problem involves finding the number of bits in the binary representation of each number from to n This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def count bits n dp n for i in range n dp i dp i gt gt i amp return dp Perfect SquaresThe Perfect Squares problem involves finding the minimum number of perfect square numbers that add up to a given number This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def num squares n dp float inf n dp for i in range n j while j j lt i dp i min dp i dp i j j j return dp n Partition Equal Subset SumThe Partition Equal Subset Sum problem involves finding whether a given set can be partitioned into two subsets such that the sum of elements in both subsets is the same This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def can partition nums n len nums s sum nums if s return False target s dp False target dp True for i in range n for j in range target nums i dp j dp j nums i return dp target Longest Common SubstringThe Longest Common Substring problem involves finding the longest substring that is common to two given strings This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def longest common substring s s m n len s len s dp n for in range m max len for i in range m for j in range n if s i s j dp i j dp i j max len max max len dp i j return max len Unique PathsThe Unique Paths problem involves finding the number of unique paths from the top left corner to the bottom right corner of a m x n grid where you can only move down or right This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def unique paths m n dp n for in range m dp for i in range m for j in range n if i gt dp i j dp i j if j gt dp i j dp i j return dp m n Edit Distance with Allowed OperationsThe Edit Distance problem can be extended to allow only a certain set of edit operations such as insertion deletion and substitution This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def edit distance with allowed ops s s allowed ops m n len s len s dp n for in range m for i in range m dp i i for j in range n dp j j for i in range m for j in range n if s i s j dp i j dp i j elif allowed ops get s i s j op cost allowed ops s i s j dp i j min dp i j op cost dp i j op cost dp i j op cost else dp i j min dp i j dp i j dp i j return dp m n Subset Sum ProblemThe Subset Sum problem involves finding whether there exists a subset of a given set of integers that adds up to a given sum This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def subset sum nums target n len nums dp False target for in range n for i in range n dp i True for i in range n for j in range target if nums i lt j dp i j dp i j nums i or dp i j else dp i j dp i j return dp n target Longest Palindromic SubstringThe Longest Palindromic Substring problem involves finding the longest substring of a given string that is a palindrome This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def longest palindromic substring s n len s dp False n for in range n max len start for i in range n dp i i True for l in range n for i in range n l j i l if l dp i j s i s j else dp i j s i s j and dp i j if dp i j and l gt max len max len l start i return s start start max len Longest Palindromic SubsequenceThe Longest Palindromic Subsequence problem involves finding the longest subsequence of a given string that is a palindrome This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def longest palindromic subsequence s n len s dp n for in range n for i in range n dp i i for l in range n for i in range n l j i l if s i s j dp i j dp i j else dp i j max dp i j dp i j return dp n Maximum Product SubarrayThe Maximum Product Subarray problem involves finding the contiguous subarray within a one dimensional array of numbers that has the largest product This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def max product subarray nums n len nums max prod nums min prod nums max so far nums for i in range n temp max prod max prod max nums i max nums i max prod nums i min prod min prod min nums i min nums i temp nums i min prod max so far max max so far max prod return max so far Largest Rectangle in a HistogramThe Largest Rectangle in a Histogram problem involves finding the largest rectangle that can be formed in a histogram composed of rectangles with different heights This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def largest rectangle area heights n len heights left n right n stack for i in range n while stack and heights stack gt heights i stack pop left i stack if stack else stack append i stack for i in range n while stack and heights stack gt heights i stack pop right i stack if stack else n stack append i max area for i in range n max area max max area heights i right i left i return max area Egg Dropping ProblemThe Egg Dropping Problem involves finding the minimum number of attempts required to find out the highest floor from which an egg can be dropped without breaking This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def egg drop n k dp k for in range n for i in range n dp i dp i for j in range k dp j j for i in range n for j in range k dp i j float inf for x in range j res max dp i x dp i j x dp i j min dp i j res return dp n k Counting BitsThe Counting Bits problem involves finding the number of bits in the binary representation of each number from to n This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def count bits n dp n for i in range n dp i dp i gt gt i amp return dp Perfect SquaresThe Perfect Squares problem involves finding the minimum number of perfect square numbers that add up to a given number This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def num squares n dp float inf n dp for i in range n j while j j lt i dp i min dp i dp i j j j return dp n Partition Equal Subset SumThe Partition Equal Subset Sum problem involves finding whether a given set can be partitioned into two subsets such that the sum of elements in both subsets is the same This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def can partition nums n len nums s sum nums if s return False target s dp False target dp True for i in range n for j in range target nums i dp j dp j nums i return dp target Unique PathsThe Unique Paths problem involves finding the number of unique paths from the top left corner to the bottom right corner of a m x n grid where you can only move down or right This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def unique paths m n dp n for in range m dp for i in range m for j in range n if i gt dp i j dp i j if j gt dp i j dp i j return dp m n Unique Paths IIThe Unique Paths II problem is a variation of the Unique Paths problem where some cells in the grid are blocked and cannot be walked on The problem involves finding the number of unique paths from the top left corner to the bottom right corner of the grid where you can only move down or right and cannot walk on blocked cells This problem can be solved using dynamic programming by breaking it down into smaller subproblems and solving each subproblem only once def unique paths with obstacles obstacle grid m n len obstacle grid len obstacle grid dp n for in range m if obstacle grid dp for i in range m for j in range n if obstacle grid i j if i gt dp i j dp i j if j gt dp i j dp i j return dp m n ConclusionDynamic Programming is a powerful technique that is essential for solving many complex problems in competitive programming The algorithms discussed in this blog are just a few of the many problems that can be solved using dynamic programming By mastering these algorithms and understanding the underlying principles you can become a better competitive programmer and solve more challenging problems	2023-04-17 06:48:59
海外TECH	DEV Community	Promises in Javascript	https://dev.to/codeofaccuracy/promises-in-javascript-2e09	Promises in JavascriptIn JavaScript a Promise is a built in object that represents the eventual completion or failure of an asynchronous operation and its resulting value It provides a cleaner and more organized way to handle asynchronous code avoiding the infamous callback hell Here s an example of how to use Promises in JavaScript const getData gt return new Promise resolve reject gt Perform an asynchronous operation such as fetching data from an API Currently we are taking static data for example const data id name Sam Adam if data If the operation is successful call the resolve method with the data resolve data else If there s an error call the reject method with the error message reject Error Unable to retrieve data Call the Promise function and handle the response using then and catch methodsgetData then data gt console log Data retrieved successfully data catch error gt console error Error occurred while retrieving data error In the example above the getData function returns a Promise object which performs an asynchronous operation of fetching data from an API If the operation is successful the Promise calls the resolve method with the data and if there s an error it calls the reject method with the error message To handle the response from the Promise you can use the then and catch methods The then method is called when the Promise is resolved successfully and it receives the data as a parameter The catch method is called when the Promise is rejected with an error and it receives the error message as a parameter Chaining Promisesconst getData gt return new Promise resolve reject gt setTimeout gt const data id name John Doe if data resolve data else reject new Error Unable to retrieve data const getDetails data gt return new Promise resolve reject gt setTimeout gt const details age city New York if details resolve data details else reject new Error Unable to retrieve details getData then getDetails then result gt console log result Output id name John Doe age city New York catch error gt console error error In the example above we have two Promises getData and getDetails that simulate fetching data from an API The getDetails Promise depends on the data returned by the getData Promise We use the then method to chain these Promises together The then method takes a callback function that returns another Promise The value returned by the first Promise is passed as an argument to the callback function of the second Promise This process can be repeated as many times as necessary We use the getData Promise to retrieve some data and then chain the getDetails Promise to retrieve additional details about that data Finally we use the then method to log the result of both Promises chained together Promise all The Promise all method allows you to run multiple Promises in parallel and wait for all of them to complete This method takes an array of Promises as its argument and returns a new Promise that is fulfilled when all of the Promises in the array have been fulfilled const promise new Promise resolve gt setTimeout resolve foo const promise const promise new Promise resolve gt setTimeout resolve bar Promise all promise promise promise then values gt console log values Output foo bar In the example above we create three Promises and pass them to the Promise all method The then method is used to log the array of values returned by the Promises when they are all fulfilled Promise race The Promise race method allows you to run multiple Promises in parallel and return the value of the first Promise that is fulfilled const promise new Promise resolve gt setTimeout resolve foo const promise new Promise resolve gt setTimeout resolve bar Promise race promise promise then value gt console log value Output foo In the example above we create two Promises and pass them to the Promise race method The then method is used to log the value of the first Promise that is fulfilled In this case promise is fulfilled first so its value foo is logged SummaryPromises are a powerful tool in JavaScript for working with asynchronous code They allow you to handle the success and failure of asynchronous operations in a more structured and readable way In addition to the then and catch methods you can also chain Promises together with the then method and run multiple Promises in parallel with the Promise all and Promise race methods	2023-04-17 06:39:17
海外TECH	DEV Community	🌟Exploring the Power of .NET Core: Unleashing the Full Potential of Cross-Platform Development🚀	https://dev.to/bhavin9920/exploring-the-power-of-net-core-unleashing-the-full-potential-of-cross-platform-development-9mn	Exploring the Power of NET Core Unleashing the Full Potential of Cross Platform DevelopmentThe rise of cross platform development has been fueled by the need to create applications that can run on multiple platforms including Windows macOS and Linux NET Core an open source cross platform framework developed by Microsoft has emerged as a popular choice among developers for building cross platform applications In this article we will explore the power of NET Core and how it can help developers unleash the full potential of cross platform development Cross Platform Capabilities One of the key benefits of NET Core is its cross platform capabilities Developers can write applications that can run on multiple platforms without having to rewrite the code for each platform This reduces development time and ensures that the application is consistent across all platforms Performance NET Core offers superior performance compared to other cross platform frameworks It uses just in time JIT compilation which compiles the code at runtime resulting in faster execution times Additionally NET Core has a smaller memory footprint making it ideal for building high performance applications Flexibility NET Core offers a high degree of flexibility allowing developers to choose the tools and libraries they prefer This means that developers can use their preferred tools such as Visual Studio Visual Studio Code or JetBrains Rider to build NET Core applications Open Source NET Core is an open source framework meaning that developers can contribute to the development of the framework and use it for free This has resulted in a vibrant community of developers who are constantly working on improving the framework Cloud Ready ️ NET Core is designed to be cloud ready which means that it can be easily deployed to cloud platforms such as Azure AWS and Google Cloud Platform This makes it ideal for building cloud native applications NET Core is a powerful cross platform framework that offers a wide range of benefits to developers Its cross platform capabilities superior performance flexibility open source nature and cloud readiness make it an ideal choice for building modern applications If you haven t tried NET Core yet now is the time to explore its full potential	2023-04-17 06:20:28
医療系	医療介護 CBnews	「外国人介護人材の受入促進と育成」を重点項目に-説明会やマッチング支援、大阪府の人材確保戦略	https://www.cbnews.jp/news/entry/20230417153813	項目	2023-04-17 15:52:00
金融	JPX マーケットニュース	[東証]制限値幅の拡大：1銘柄	https://www.jpx.co.jp/news/1030/20230417-01.html	東証	2023-04-17 15:15:00
金融	JPX マーケットニュース	[TOCOM]最終決済価格（2023年5月限）：LNG（プラッツJKM）	https://www.jpx.co.jp/markets/derivatives/special-quotation/index.html	jkmtocom	2023-04-17 15:15:00
金融	日本銀行：RSS	【記者会見】植田総裁（G20、4月13日分）	http://www.boj.or.jp/about/press/kaiken_2023/kk230417a.pdf	記者会見	2023-04-17 15:40:00
ビジネス	東洋経済オンライン	私の中に｢天使と悪魔｣育児に悩む母の荒ぶる内心 漫画｢学校に行かない君が教えてくれたこと｣（第3話） | 学校に行かない君が教えてくれたこと | 東洋経済オンライン	https://toyokeizai.net/articles/-/664461?utm_source=rss&utm_medium=http&utm_campaign=link_back	君が教えてくれた	2023-04-17 15:30:00
ニュース	Newsweek	ロシア軍関連施設で相次ぐ不審火。反プーチン勢力「黒い橋」の犯行声明も	https://www.newsweekjapan.jp/stories/world/2023/04/post-101419.php	地元当局は月、プーチンが月に出した部分動員令を受けてウクライナでの戦闘に動員された一部の住民がカザンに送られたと明らかにしている。	2023-04-17 15:23:42
マーケティング	MarkeZine	スマホで撮った動画、20代の6割がネット投稿／4割が縦画面で撮影【ロイヤリティ マーケティング調査】	http://markezine.jp/article/detail/41988	画面	2023-04-17 15:15:00
IT	週刊アスキー	おしゃれな街、丸の内で大人のオリジナルカクテルを！　東京ステーションホテルのバー＆カフェ「カメリア」で提供	https://weekly.ascii.jp/elem/000/004/133/4133154/	東京ステーションホテル	2023-04-17 15:50:00
IT	週刊アスキー	シューティングライクRPG『エラーゲームリセット』の配信日が4月25日に決定！	https://weekly.ascii.jp/elem/000/004/133/4133152/	gamereset	2023-04-17 15:45:00
IT	週刊アスキー	Twitter、ツイート最大1万字に 「Twitter Blue」会員限定	https://weekly.ascii.jp/elem/000/004/133/4133166/	twitter	2023-04-17 15:45:00
IT	週刊アスキー	『ウマ娘』新CMシリーズ「Glories」の第2弾「テイエムオペラオー篇」が放送開始	https://weekly.ascii.jp/elem/000/004/133/4133141/	cygames	2023-04-17 15:30:00
IT	週刊アスキー	『ウマ娘』新作アニメが公式YouTubeチャンネルで無料配信開始！	https://weekly.ascii.jp/elem/000/004/133/4133138/	cygames	2023-04-17 15:25:00
マーケティング	AdverTimes	花王グループ 「刺さる」流通提案の必須事項	https://www.advertimes.com/20230417/article416529/	試行錯誤	2023-04-17 06:35:44