投稿時間:2022-06-18 23:07:31 RSSフィード2022-06-18 23:00 分まとめ(9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	Pythonを用いて母比率の信頼区間を求める 〜ナンパの成功確率〜	https://qiita.com/ta10ko/items/4de50aab815a824c01fc	信頼区間	2022-06-18 22:12:09
Ruby	Rubyタグが付けられた新着投稿 - Qiita	Rubyでスレッドセーフでないコードを実行するとどうなる？	https://qiita.com/rihofujino/items/8148699751dce37f66af	複数	2022-06-18 22:57:04
AWS	AWSタグが付けられた新着投稿 - Qiita	円安の今だから読みたいAWS Well-Architected コスト最適化の柱	https://qiita.com/yoshii0110/items/bfac45e63bc0a079fdd6	awswellarchitected	2022-06-18 22:40:15
AWS	AWSタグが付けられた新着投稿 - Qiita	Exam Readiness AWS Advanced Networking Overview (Japanese)のまとめ	https://qiita.com/tetsuya_tech/items/0533b88d8dc7597116cd	awsdop	2022-06-18 22:14:12
Docker	dockerタグが付けられた新着投稿 - Qiita	続：PostgreSQLをデータごとDockerコンテナ化する	https://qiita.com/oohira/items/64a387fee59df3399807	docker	2022-06-18 22:47:15
Git	Gitタグが付けられた新着投稿 - Qiita	.gitignoreでフォルダの構造のみを保持したい場合のより良い書き方	https://qiita.com/silane1001/items/ba37ecfec218634a9d94	gitignore	2022-06-18 22:24:22
海外TECH	MakeUseOf	The 7 Reasons Why Your Phone Battery Is Draining So Fast	https://www.makeuseof.com/why-phone-battery-draining-fast/	battery	2022-06-18 13:20:13
海外TECH	DEV Community	10 Algorithms Every Developer Should Learn	https://dev.to/codesphere/10-algorithms-every-developer-should-learn-3lnm	Algorithms Every Developer Should LearnThere seems to be a large misconception from a lot of aspiring devs that memorizing standard algorithms is important Now for some job interviews that may be the case but it is not particularly important for actually being a successful developer So are the things you learn in an algorithm class useless Absolutely not What is incredibly important is the ability to think algorithmically Not just so that you can reproduce and altar standard algorithms but so that you are comfortable using code to solve whatever problems you encounter as a dev That s why we ve assembled a list of algorithms that aspiring devs should work through to get comfortable with thinking algorithmically Binary SearchBinary search is one of the first things taught in any computer science class It is perhaps the simplest example of how a little bit of ingenuity can make things quite literally exponentially more efficient A binary search consists of taking a sorted array and iteratively splitting the array into two and comparing an element that you are looking for against each half until you find the element Selection Bubble and Insertion SortSorting algorithms are one of the most fundamental tools that a developer should have in their arsenal Selection Bubble and Insertion sort are some of the first that new developers should work through In any scenario when speed matters you re not going to be using these algorithms but working with them is a great introduction to array traversal and manipulation Quicksort and MergesortSimilar to sorting algorithms are great for getting comfortable with arrays but Quicksort and Mergesort are efficient enough to be used in serious applications Being comfortable implementing these sorting algorithms Note Being comfortable and not memorizing these algorithms are essential to being a serious developer Huffman CodingHuffman coding is the foundation of modern text compression It works by considering how often different characters appear in a text and organizes them in a tree based on this frequency Breadth First SearchAgain trees turn out to be at the heart of a lot of algorithms and software that developers work with As such understanding basic tree traversal is a top priority for an aspiring developer Breadth first search works by exploring a tree level by level until the target node is found Since it literally going through every level it is guaranteed to find a solution Depth First SearchContinuing with tree traversal Depth First Search is the other main approach for finding an element in a tree Instead of working down the tree level by level it explores the tree branch by branch Now assuming it does not have infinitely extended branches DFS will similarly always work Implementing these two search algorithms aren t particularly complex but what is incredibly important is learning when to use one over the other A lot of software design is being able to understand the structure of the information you are working with and pick algorithms that optimize for that structure Gradient DescentNow for a lot of developers Gradient Descent is not necessarily going to be useful If however you are touching anything with regression or machine learning Gradient Descent is going to be at the heart of your work Gradient Descent is a method of procedure optimizing functions using calculus In the context of regression and machine learning this means finding specific values that minimize the error in your prediction algorithm While it is certainly more mathematically involved that a lot of these other algorithms if you are working significantly with data and predictions understanding how gradient descent works is incredibly important Dijkstra s AlgorithmAnother incredibly important issue that developers work with is path finding Graphs turn out to be an incredibly versatile way to describe all kinds of problems that involve networks of distinct objects Dijkstra s algorithm is a way of finding the quickest path between two nodes in a graph It is the foundation of most work done in path finding and finds itself used in anything from artificial intelligence to game design Diffie Helllman Key ExchangeThe Diffie Hellman Key Exchange is a great introduction to how cryptography tends to work More specifically a Diffie Hellman Key Exchange works by combining public and private keys Which are effectively long numbers to encrypt information when it is being transferred between different parties Even if you re not working in cybersecurity having a working understanding of encryption and secure communication is incredibly important to working as a developer Additionally even though Diffie Helman is far from the best algorithm it is incredibly easy to implement and is similar enough to most other encrypted communication methods Doing Practice ProblemsThese first nine algorithms all gave you ways to solve archetypes of problems you might encounter as a developer The reality however is that as a developer you are often going to be encountering algorithmic problems that are completely new That s why more important than memorizing any algorithm is developing the ability to solve problems algorithmically Luckily there is no shortage of websites to practice Some of our favorites are More mathematical These are great environments to find difficult yet fulfilling algorithmic problems and hone your skills So Now What Again do not just memorize these algorithms and think you are suddenly a better developer for it Software Engineering first and foremost is about being able to understand problems and build solutions Learning algorithms isn t important because you are going to have to exactly implement them for something you re building They are important because they teach you how to approach problems What did we leave off the list Let us know down below As always happy coding from your friends at Codesphere the swiss army knife every development team needs	2022-06-18 13:38:50
ニュース	BBC News - Home	Naomi Osaka withdraws from Wimbledon with Achilles injury	https://www.bbc.co.uk/sport/tennis/61852544?at_medium=RSS&at_campaign=KARANGA	achilles	2022-06-18 13:27:52