関数名、メソッド名、変数名でよく使う英単語のまとめ
プログラミングをしていると関数名、メソッド名、変数名をどうするか悩みます。 ロジックより命名に時間を費やすこともざらにあります。翻訳したり、一般的な命名規則なのかいつも検索して大変です。 よく使うサイトの内容をコピってメモしておく 関数名とメソッド名の違いについて よく使う英単語のまえに、いつもごっちゃにして使っているけど、定義はこんな感じ 「関数」と「メソッド」の違い 似ているところ どちらも何か（引数）を入れると処理をして何か（戻り値）を返してくれます。 違うところ やってること自体は大差ありません。概念としては違います。 メソッドはオブジェクト指向で登場する用語で、オブジェクトの動作を定義したものです。 まずオブジェクトありきなのですね。一方の関数は、オブジェクト云々は関係ありません。 個人的な使い分け Java で登場する関数は「メソッド」です。C 言語で登場する関数は「関数」と呼
Deleted articles cannot be recovered. Draft of this article would be also deleted. Are you sure you want to delete this article? LLMs The History of Chatbots ELIZA (1966) 初期の人工知能プログラムのひとつ。 ルールベースの簡単なパターンマッチングで返答していた。 心理療法士の会話を模したELIZA(DOCTOR)が有名。 PARRY (1972) PARRYは偏執病的統合失調症患者をシミュレートしようとしたもの。 ELIZA(DOCTOR)と通信し話題となった。 Jabberwacky (1982, 1988, 1997) ユーモラスな人間同士の自然な会話をシミュレートすることを目的としていた。 ユーザーとの会話の大規模な
OpenAI API ドキュメントの日本語訳をこちらでまとめます。文字量の多いドキュメントなので、セクションごとに記事を分割しています。 今回は「GET STARTED 」のセクションからLibraries 、Models、TutorialsそしてUsage policiesを抜粋した後編です。 基本 DeepLで翻訳して、気になるところだけ書き換えています(ほぼ気になるところがないのが、DeepLのすごいところ)。原文との突き合わせができるようにはじめに原文を入れてますので、間違いなど見つけられましたら、ぜひご指摘ください。ご指摘箇所は随時反映させていただきます。 原文のリンクが有効になってますので、それぞれ必要な場合は原文リンクの方を参照ください。 前回のおさらいはこちら Python library｜Python ライブラリWe provide a Python library, w
Announcing New Tools for Building with Generative AI on AWS | Amazon Web Services
Artificial Intelligence Announcing New Tools for Building with Generative AI on AWS The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of scalable compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are transforming their businesses. Just recently, generative AI appli
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
awesome-scalability
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems View the Project on GitHub View On GitHub An updated and organized reading list for illustrating the patterns of scalable, reliable, and performant large-scale systems. Concepts are explained in the articles of prominent engineers and credible references. Case studies are taken from battle-tested systems that serve millions to
the peculiar case of japanese web design a project that should not have taken 8 weeks how is japanese web design different? in this 2013 Randomwire blog post, the author (David) highlighted an intriguing discrepancy in Japanese design. While the nation is known abroad for minimalist lifestyles, their websites are oddly maximalist. The pages feature a variety of bright colours (breaking the 3 colou
Incident Metrics in SRE
Štěpán Davidovič Incident Metrics in SRE Critically Evaluating MTTR and Friends Boston Farnham Sebastopol Tokyo Beijing Boston Farnham Sebastopol Tokyo Beijing 978-1-098-10313-2 [LSI] Incident Metrics in SRE by Štěpán Davidovič Copyright © 2021 O’Reilly Media, Inc. All rights reserved. Printed in the United States of America. Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebas
GitHub - opendatalab/MinerU: A high-quality tool for convert PDF to Markdown and JSON.一站式开源高质量数据提取工具，将PDF转换成Markdown和JSON格式。
2025/08/01 2.1.10 Released Fixed an issue in the pipeline backend where block overlap caused the parsing results to deviate from expectations #3232 2025/07/30 2.1.9 Released transformers 4.54.1 version adaptation 2025/07/28 2.1.8 Released sglang 0.4.9.post5 version adaptation 2025/07/27 2.1.7 Released transformers 4.54.0 version adaptation 2025/07/26 2.1.6 Released Fixed table parsing issues in ha
Agents
Intelligent agents are considered by many to be the ultimate goal of AI. The classic book by Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (Prentice Hall, 1995), defines the field of AI research as “the study and design of rational agents.” The unprecedented capabilities of foundation models have opened the door to agentic applications that were previously unimaginabl
Patterns for Building LLM-based Systems & Products [ llm engineering production 🔥 ] · 66 min read Discussions on HackerNews, Twitter, and LinkedIn “There is a large class of problems that are easy to imagine and build demos for, but extremely hard to make products out of. For example, self-driving: It’s easy to demo a car self-driving around a block, but making it into a product takes a decade.”
Introducing Amazon Nova foundation models: Frontier intelligence and industry leading price performance | Amazon Web Services
AWS News Blog Introducing Amazon Nova foundation models: Frontier intelligence and industry leading price performance April 23, 2025: Post updated to include benchmark evaluations for the understanding models at the time of launch. Today, we’re thrilled to announce Amazon Nova, a new generation of state-of-the-art foundation models (FMs) that deliver frontier intelligence and industry leading pric
Real-world gen AI use cases from the world's leading organizations | Google Cloud Blog
AI is here, AI is everywhere: Top companies, governments, researchers, and startups are already enhancing their work with Google's AI solutions. Published April 12, 2024; last updated October 9, 2025. A year and a half ago, during Google Cloud Next 24, we published this list for the first time. It numbered 101 entries. It felt like a lot at the time, and served as a showcase of how much momentum b
PyTorch 2.0
Overview Introducing PyTorch 2.0, our first steps toward the next generation 2-series release of PyTorch. Over the last few years we have innovated and iterated from PyTorch 1.0 to the most recent 1.13 and moved to the newly formed PyTorch Foundation, part of the Linux Foundation. PyTorch’s biggest strength beyond our amazing community is that we continue as a first-class Python integration, imper
One of FLAML’s algorithms CFO tuning the # of leaves and the # of trees for XGBoost. The two heatmaps show the loss and cost distribution of all configurations. The black dots are the points evaluated in CFO. Black dots connected by lines are points that yield better loss performance when evaluated (image by authors).Authors: Qingyun Wu, Chi Wang, Antoni Baum, Richard Liaw and Michael Galarnyk FLA
For demonstration purposes, we'll fine-tune the multilingual version of the small checkpoint with 244M params (~= 1GB). As for our data, we'll train and evaluate our system on a low-resource language taken from the Common Voice dataset. We'll show that with as little as 8 hours of fine-tuning data, we can achieve strong performance in this language. 1{}^11 The name Whisper follows from the acronym
Hermit: Deterministic Linux for Controlled Testing and Software Bug-finding
Hermit: Deterministic Linux for Controlled Testing and Software Bug-finding If you've used emulators for older platforms, you probably experienced a level of precise control over software execution that we lack on contemporary platforms. For example, if you play 8-bit video games emulated on your modern console, you are able to suspend and rewind gameplay, and when you resume, that incoming creatu
単語埋め込みのライブラリ whatlies を調べてみた
先日、Twitterでtransformersとscikit-learnをscikit-learnのPipelineを使って組み合わせることができることを知りました。 I made a small proof-of-concept of how @huggingface transformers can be combined with scikit-learn classifiers on top and then later wrapped with scikit-learn pipelines https://t.co/PnC1PFv2uA — merve 💛 (@mervenoyann) June 14, 2022 構成としては、transformersのモデルの最終層のアウトプットを特徴量としてscikit-learnのモデルに渡すというよくあるパターンだと思うのですが、tra
Python support GA: improving Python code quality using Amazon CodeGuru Reviewer | Amazon Web Services
AWS DevOps & Developer Productivity Blog Python support GA: improving Python code quality using Amazon CodeGuru Reviewer We are pleased to announce the GA launch of Python support in Amazon CodeGuru Reviewer, a service that helps you improve source code quality by automatically detecting hard-to-find defects. CodeGuru Reviewer is powered by program analysis and machine learning, and trained on bes
Mastering Customer Segmentation with LLM | Towards Data Science
Unlock advanced customer segmentation techniques using LLMs, and improve your clustering models with advanced techniques Content Table · Intro · Data · Method 1: Kmeans · Method 2: K-Prototype · Method 3: LLM + Kmeans · Conclusion Intro A customer segmentation project can be approached in multiple ways. In this article I will teach you advanced techniques, not only to define the clusters, but to a
Understanding what software salaries developer in Japan are be tricky. As a whole, software development doesn’t pay exceptionally well: according to [a 2023 survey](https://www.e-stat.go.jp/stat-search/files?page=1&layout=datalist&toukei=00450091&tstat=000001011429&cycle=0&tclass1=000001213360&tclass2=000001215880&tclass3=000001215884&tclass4val=0) conducted by the Ministry of Health, Labor and We
As Elixir's Machine Learning (ML) ecosystem grows, many Elixir enthusiasts who wish to adopt the new machine learning libraries in their projects are stuck at a crossroads of wanting to move away from their existing ML stack (typically Python) while not having a clear path of how to do so. I would like to take some time to talk to WHY I believe now is a good time to start porting over Machine Lear
Noble Numbat Release Notes Table of Contents Introduction New features in 24.04 LTS Known Issues Official flavours More information Introduction These release notes for Ubuntu 24.04 LTS (Noble Numbat) provide an overview of the release and document the known issues with Ubuntu and its flavours. For details of the changes applied since 24.04, please see the 24.04.2 change summary. Support lifespan
Below is part 1 of an extended scenario describing how the future might go if current trends in AI continue. The scenario is deliberately extremely specific: it’s definite rather than indefinite, and makes concrete guesses instead of settling for banal generalities or abstract descriptions of trends. Open Sky. (Zdzisław Beksiński)The return of reinforcement learningFrom 2019 to 2023, the main driv
GitHub - mediacms-io/mediacms: MediaCMS is a modern, fully featured open source video and media CMS, written in Python/Django and React, featuring a REST API.
Complete control over your data: host it yourself! Modern technologies: Django/Python/Celery, React. Support for multiple publishing workflows: public, private, unlisted and custom Multiple media types support: video, audio, image, pdf Multiple media classification options: categories, tags and custom Multiple media sharing options: social media share, videos embed code generation Video Trimmer: t
Version 1.0
Version 1.0# For a short description of the main highlights of the release, please refer to Release Highlights for scikit-learn 1.0. Legend for changelogs Major Feature something big that you couldn’t do before. Feature something that you couldn’t do before. Efficiency an existing feature now may not require as much computation or memory. Enhancement a miscellaneous minor improvement. Fix somethin
Deconstructing prompt-based meta-tool architecture and context injection patterns for AI engineering - Claude’s Agent Skills system represents a sophisticated prompt-based meta-tool architecture that extends LLM capabilities through specialized instruction injection. Unlike traditional function calling or code execution, skills operate through prompt expansion and context modification to modify ho
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歴代チャットボットと最近のLLMのまとめ - Qiita
OpenAI API ドキュメント 日本語訳｜#2 GET STARTED 後編｜ゑぐみかるちゃあ
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Fine-Tune Whisper For Multilingual ASR with 🤗 Transformers
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From Python to Elixir Machine Learning
Ubuntu 24.04 LTS (Noble Numbat) Release Notes
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