こんにちは。サービスグループの武田です。このエントリは、2018年から公開しているAWS全サービスまとめの2022年版です。 こんにちは。サービスグループの武田です。 このエントリは、2018年から毎年公開している AWS全サービスまとめの2022年版 です。昨年までのものは次のリンクからたどってください。 AWSにはたくさんのサービスがありますが、「結局このサービスってなんなの？」という疑問を自分なりに理解するためにまとめました。 今回もマネジメントコンソールを開き、「サービス」の一覧をもとに一覧化しました。そのため、プレビュー版など一覧に載っていないサービスは含まれていません。また2021年にまとめたもののアップデート版ということで、新しくカテゴリに追加されたサービスには[New]、文章を更新したものには[Update]を付けました。ちなみにサービス数は 223個 です。 まとめるにあ
BigQueryの新発表を解説（Google Cloud Next '25速報） - G-gen Tech Blog
G-gen の杉村です。当記事では、Google Cloud Next '25 で発表された BigQuery の新機能について紹介します。 概要 BigQuery と AI の統合 全体像 BigQuery data preparation データセットレベルのインサイト（BigQuery データキャンバス） BigQuery pipelines にデータエンジニアリングエージェントが組み込み Colab Notebook にデータサイエンスエージェントが組み込み BigQuery AI query engine BigQuery DataFrames におけるコード支援 Looker の会話型分析 SQL 移行アシスト データガバナンス Dataplex Catalog が BigQuery universal catalog に改名 Automated metadata curati
何年後かの自分へ こんにちは、のんピ(@non____97)です。 業務で使用する新しいMacが届きました。 新しいMacを初期セットアップするにあたって「今の設定どうだったっけ...」と調べる時間が結構かかってしまいました ということで何年後かの自分がまた新しいMacに乗り換える際に手間取らないように、設定した内容を書き記しておきます。 移行先のMacの情報は以下の通りです。M1 Max、嬉しい。 # OSのバージョンの確認 > sw_vers ProductName: macOS ProductVersion: 12.4 BuildVersion: 21F79 # カーネルのバージョン確認 > uname -r 21.5.0 # CPUのアーキテクチャの確認 > uname -m arm64 # CPUの詳細確認 > sysctl -a machdep.cpu machdep.cpu.
Making of “Kindolphin” | 麦 Baku
group_inou / HAPPENING group_inouとAC部のミュージックビデオ作品『HAPPENING』をWebアプリ化しました。デザインと実装は僕一人です。元のビデオがGIFアニメ縦長漫画が歌詞に合わせて自動スクロールする仕様だったので、GIFの質感をロスレスかつ自分のペースで楽しめるように、某電子書籍アプリのような体裁でインタラクションできるようにした次第です。 We have just released a Webtoon app that highlights the lyrics of group_inou's music video "HAPPENING". You can switch between Japanese/English, change colors, stop and have a close look, or just scratch and
GitHub - modelcontextprotocol/servers: Model Context Protocol Servers
Official integrations are maintained by companies building production ready MCP servers for their platforms. 21st.dev Magic - Create crafted UI components inspired by the best 21st.dev design engineers. ActionKit by Paragon - Connect to 130+ SaaS integrations (e.g. Slack, Salesforce, Gmail) with Paragon’s ActionKit API. Adfin - The only platform you need to get paid - all payments in one place, in
January 30, 2023 In this post, we'll implement a GPT from scratch in just 60 lines of numpy. We'll then load the trained GPT-2 model weights released by OpenAI into our implementation and generate some text. Note: This post assumes familiarity with Python, NumPy, and some basic experience with neural networks. This implementation is for educational purposes, so it's missing lots of features/improv
- はじめに - Rustでグラフを描画したいと思った時に調べたクレートとその実装、機能のまとめた時のメモ。 現状はplottersを使っておけば間違いなさそうだが、目的によっては機能で選択する場合もありそう。 - はじめに - - 前提知識 - - グラフ描画クレートざっくりまとめ - plotters plotly plotlib poloto rustplotlib RustGnuplot preexplorer vega_lite_4.rs dataplotlib chord_rs - アスキーアート系のクレート - - 記事外で参考になりそうな記事 - - おわりに - - 前提知識 - グラフの描画までの機能としては、matplotlibのようにaxisやviewを構造体として持っているライブラリもあれば、受け取った配列をそのままgnuplotのスクリプトに変換するライブラリも
ボードゲームのデータ解析その2：BGGの複雑さに関するバイアス(An analysis of board games: Part II - Complexity bias in BGG)｜べよ
本記事は、Dinesh Vatvani氏が2018年12月8日に投稿した「An analysis of board games: Part II - Complexity bias in BGG」の翻訳である。引き続き、BGGのデータ分析の話である。今回の記事は、BGGの上位100ゲームにメスを入れた話となっている。 BGGの上位100ゲームのリストは、私たちボードゲーマーにとって有益な指標となっているし、出版社・ボードゲームデザイナーにとってもステイタスになっている。ただ、上位100ゲームを見ると、複雑なゲーム、いわゆる重ゲーが圧倒的に多い。裏を返せば、少なくとも、BGG上の評価を得るためには、重ゲーを製作する必要があるように思えてしまう。 このように、BGGには複雑なゲームを好む傾向があるのか(複雑さバイアス)ということをデータから分析してみようというのが本記事の内容である。その上で、
Join a VS Code Dev Days event near you to learn about AI-assisted development in VS Code. Update 1.67.1: The update addresses this security issue. Update 1.67.2: The update addresses these issues. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the April 2022 release of Visual Studio Code. There are many updates in this version that we hope
Release date: June 12, 2025 Security update: The following extension has security updates: ms-python.python. Update 1.101.1: The update addresses these issues. Update 1.101.2: The update addresses these issues. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the May 2025 release of Visual Studio Code. There are many updates in this version
こんにちは。サービス開発室の武田です。 このエントリは、2018年から毎年公開している AWS全サービスまとめの2025年版 です。昨年までのものは次のリンクからたどってください。 AWSにはたくさんのサービスがありますが、「結局このサービスってなんなの？」という疑問を自分なりに理解するためにまとめました。 今回もマネジメントコンソールを開き、「サービス」の一覧をもとに一覧化しました。そのため、プレビュー版など一覧に載っていないサービスは含まれていません。また2024年にまとめたもののアップデート版ということで、新しくカテゴリに追加されたサービスには[New]、文章を更新したものには[Update]を付けました。ちなみにサービス数は 250個 です。 まとめるにあたって、次のドキュメントや、弊社の多数のブログを参考にしました。 コンピューティング Amazon EC2 正式名称は Amaz
Jupyter Notebooks in Microsoft Excel. Image by the author.It used to be an “either/or” choice between Excel and Python Jupyter Notebooks. With the introduction of the PyXLL-Jupyter package now you can use both together, side by side. In this article I’ll show you how to set up Jupyter Notebooks running inside Excel. Share data between the two and even call Python functions written in your Jupyter
Join a VS Code Dev Days event near you to learn about AI-assisted development in VS Code. Update 1.58.1: The update addresses these security issues. Update 1.58.2: The update addresses these issues. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the June 2021 release of Visual Studio Code. There are a number of updates in this version that
Exactly ten years ago today, we published "Why We Created Julia", introducing the Julia project to the world. At this point, we have moved well past the ambitious goals set out in the original blog post. Julia is now used by hundreds of thousands of people. It is taught at hundreds of universities and entire companies are being formed that build their software stacks on Julia. From personalized me
Update 1.87.1: The update addresses these issues. Update 1.87.2: The update addresses this security issue. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the February 2024 release of Visual Studio Code. There are many updates in this version that we hope you'll like, some of the key highlights include: Voice dictation in editor - Use your
Data dashboarding tools | Streamlit v.s. Dash v.s. Shiny vs. Voila vs. Flask vs. Jupyter
Just tell me which one to useAs always, “it depends” – but if you’re looking for a quick answer, you should probably use: Dash if you already use Python for your analytics and you want to build production-ready data dashboards for a larger company.Streamlit if you already use Python for your analytics and you want to get a prototype of your dashboard up and running as quickly as possible.Shiny if
A Lisp REPL as my main shell
If you enjoy this article and would like to help me keep writing, consider chipping in, every little bit helps to keep me going :) Thank you! Update: As of 2021-02-07, not all the code and configurations used in this presentation have been published. Should happen in the coming days, stay tuned! Introduction video The concepts I’m going to present in this article were featured in a presentation at
Introducing AWS Glue Auto Scaling: Automatically resize serverless computing resources for lower cost with optimized Apache Spark | Amazon Web Services
AWS Big Data Blog Introducing AWS Glue Auto Scaling: Automatically resize serverless computing resources for lower cost with optimized Apache Spark October 2024: This post has been updated along with Interactive Sessions support for AWS Glue Auto scaling. June 2023: This post was reviewed and updated for accuracy. Data created in the cloud is growing fast in recent days, so scalability is a key fa
Plan 9 Desktop Guide
PLAN 9 DESKTOP GUIDE INDEX What is Plan 9? Limitations and Workarounds Connecting to Other Systems VNC RDP SSH 9P Other methods Porting Applications Emulating other Operating Systems Virtualizing other Operating Systems Basics Window Management Copy Pasting Essential Programs Manipulating Text in the Terminal Acme - The Do It All Application Multiple Workspaces Tiling Windows Plumbing System Admin
Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Update 1.72.1: The update addresses these security issues. Update 1.72.2: The update addresses these issues. Welcome to the September 2022 release of Visual Studio Code. There are many updates in this version that we hope you'll like, some of the key highlights include: Tool bar customization - Hide/show
TL;DR Geminiの有料プランGemini Advancedでは、5/14から100万トークンもの入力に対応したGemini 1.5 Proを提供開始、更に5/21からスプレッドシートをアップロードしてのデータ分析や可視化が可能になりました。これはPythonのコードを生成して実行するする機能です。 データ分析の性能としてはGemini AdvancedはChatGPT-4oとほぼ同等の性能でどんぐりの背比べ甲乙が付け難いです。Geminiの場合、Google Sheetsなどと連携でき、データの取り込みやエクスポートが容易です。一方のChatGPTは、可視化したグラフがより見やすい印象です。 しかし、Gemini AdvancedもChatGPT-4oも指示が曖昧では適切な集計ができないなど、データサイエンティストの視点から見ると、生成AIに任せきりでは不安な点が多く見受けられます
AWS News Blog New — Amazon Athena for Apache Spark When Jeff Barr first announced Amazon Athena in 2016, it changed my perspective on interacting with data. With Amazon Athena, I can interact with my data in just a few steps—starting from creating a table in Athena, loading data using connectors, and querying using the ANSI SQL standard. Over time, various industries, such as financial services, h
How to create a dashboard in Python with Jupyter Notebook? Would you like to build a data dashboard in 9 lines of Python code? I will show you how to create a dashboard in Python with Jupyter Notebook. The dashboard will present information about stock for selected ticker (data table and chart). The notebook will be published as a web application. I will use an open-source Mercury framework to con
JupyterLab Changelog — JupyterLab 4.5.0a3 documentation
JupyterLab Changelog# v4.4# JupyterLab 4.4 includes a number of new features (described below), bug fixes, and enhancements. This release is compatible with extensions supporting JupyterLab 4.0. Extension authors are encouraged to consult the Extension Migration Guide which lists deprecations and changes to the public API. Code console improvements# The code console prompt can now be positioned on
Pandas DataFrame Visualization Tools - Practical Business Python
Introduction I have talked quite a bit about how pandas is a great alternative to Excel for many tasks. One of Excel’s benefits is that it offers an intuitive and powerful graphical interface for viewing your data. In contrast, pandas + a Jupyter notebook offers a lot of programmatic power but limited abilities to graphically display and manipulate a DataFrame view. There are several tools in the
Dive deep into AWS Glue 4.0 for Apache Spark | Amazon Web Services
AWS Big Data Blog Dive deep into AWS Glue 4.0 for Apache Spark Jul 2023: This post was reviewed and updated with Glue 4.0 support in AWS Glue Studio notebook and interactive sessions. Deriving insight from data is hard. It’s even harder when your organization is dealing with silos that impede data access across different data stores. Seamless data integration is a key requirement in a modern data
Artificial Intelligence Data processing options for AI/ML This blog post was reviewed and updated June, 2022 to include new features that have been added to the Data processing such as Amazon SageMaker Studio and EMR integration. Training an accurate machine learning (ML) model requires many different steps, but none are potentially more important than data processing. Examples of processing steps
Release date: July 9, 2025 Update 1.102.1: The update addresses these issues. Update 1.102.2: The update addresses these issues. Update 1.102.3: The update addresses these issues. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the June 2025 release of Visual Studio Code. There are many updates in this version that we hope you'll like, some
Data engineering at Meta: High-Level Overview of the internal tech stack
Data engineering at Meta: High-Level Overview of the internal tech stack This article provides an overview of the internal tech stack that we use on a daily basis as data engineers at Meta. The idea is to shed some light on the work we do, and how the tools and frameworks contribute to making our day-to-day data engineering work more efficient, and to share some of the design decisions and technic
Track Awesome List Updates DailyWe track over 500 awesome list updates, and you can also subscribe to daily or weekly updates via RSS or News Letter. This repo is generated by trackawesomelist-source, visit it Online or with Github. 📅 Weekly · 🔍 Search · 🔥 Feed · 📮 Subscribe · ❤️ Sponsor · 😺 Github · 🌐 Website · 📝 07/29 · ✅ 07/29 Table of Contents Recently Updated Top 50 Awesome List All Tr
Here’s why. As enterprises become more agile, centralization appears more and more as a thing of the past world, a waterfall world. The same appears to be true with data platforms. Therefore, we are building a Data Mesh, this next generation of data platforms for PayPal Credit. This post details the evolution of data platforms, highlights their problems, and why we decided to build a Data Mesh. I
v2022: Austin Huang, Suraj Subramanian, Jonathan Sum, Khalid Almubarak, and Stella Biderman. Original: Sasha Rush. The Transformer has been on a lot of people’s minds over the last year five years. This post presents an annotated version of the paper in the form of a line-by-line implementation. It reorders and deletes some sections from the original paper and adds comments throughout. This docume
Python VS Common Lisp, workflow and ecosystem - Lisp journey
NEW: 9 videos (86min) about CLOS on my Common Lisp course. Out of 7h+ of content. Rated 4.7/5. Learn more and stay tuned. 🎥 I also have cool Lisp showcases on Youtube . The last ones: how to build a web app in Common Lisp, part 1 and 2. I learned Java and C at school, I learned Python by myself and it was a relief. After 8 years working and doing side projects in Python and JavaScript (mostly web
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【2022年】AWS全サービスまとめ | DevelopersIO
ぼくのMac環境 ver.のんピ | DevelopersIO
GPT in 60 Lines of NumPy | Jay Mody
Rustでグラフをplotするライブラリのまとめ - Stimulator
April 2022 (version 1.67)
May 2025 (version 1.101)
【2025年】AWS全サービスまとめ | DevelopersIO
Python Jupyter Notebooks in Excel
June 2021 (version 1.58)
Why We Use Julia, 10 Years Later
February 2024 (version 1.87)
September 2022 (version 1.72)
Gemini Advancedでデータ分析をやってみた - GMOインターネットグループ グループ研究開発本部
New — Amazon Athena for Apache Spark | Amazon Web Services
How to create a dashboard in Python with Jupyter Notebook? | MLJAR
Data processing options for AI/ML | Amazon Web Services
June 2025 (version 1.102)
Track Awesome List Updates Daily
The next generation of Data Platforms is the Data Mesh
The Annotated Transformer