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GitHub - dair-ai/Prompt-Engineering-Guide: 🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skills help to better understand the capabilities and limitations of large language models (LLMs). Researchers use prompt engineering to improve the capacity of LLMs on a wide range of common and
データサイエンス100本ノックを、Google ColabとAzure Notebooksで気軽に行いたい！ - Qiita
データサイエンス100本ノックを、Google ColabとAzure Notebooksで気軽に行いたい！PythonAzureデータサイエンス100本ノックGoogleColaboratory はじめに 2020年6月15日に、データサイエンティスト協会より発表されました「データサイエンス100本ノック（構造化データ加工編）」の素晴らしさに感動した私は早速ドリルを解き、めくるめくデータサイエンスの大冒険をエンジョイしていた。 しかし、ふと気づくとOriginalのデータサイエンス100本ノック（構造化データ加工編）はDocker形式で提供されており、実践的な演習が可能である一方でお手軽感はかった。同じ思いの人も数多く存在すると考え、より気軽に100本ノックするためにGoogle ColabとAzure Notebookで実行可能な演習スクリプトと解答編スクリプトを作成した。なお、作成者
GitHub - fastai/fastbook: The fastai book, published as Jupyter Notebooks
These notebooks cover an introduction to deep learning, fastai, and PyTorch. fastai is a layered API for deep learning; for more information, see the fastai paper. Everything in this repo is copyright Jeremy Howard and Sylvain Gugger, 2020 onwards. A selection of chapters is available to read online here. The notebooks in this repo are used for a MOOC and form the basis of this book, which is curr
VSCodeの拡張機能としてJupyter NotebookをベースにJavaScript/Mermaid/SQLなど多言語対応にした「Polyglot Notebooks」が正式リリース
VSCodeの拡張機能としてJupyter NotebookをベースにJavaScript/Mermaid/SQLなど多言語対応にした「Polyglot Notebooks」が正式リリース Jupyter Notebookはシンプルなエディタ画面にPythonやScala、Rなどのコードを打ち込んですぐに実行できる、インタラクティブなコード実行環境で、特にデータサイエンティストなどで重宝されているツールです。 結果も同じNotebook上に表やグラフ形式で表示可能なのに加えて、Markdown/LateX/HTMLなどを記述することでリッチなテキスト表現と画像や動画の埋め込みなどもできます。 このJupyter Notebookをベースに、C#やF#、JavaScript、Mermaid、SQLなど、さらに多くのプログラミング言語やマークアップ言語への対応を行ったVisual Studio
GitHub - cmoog/vscode-sql-notebook: Open SQL files as VSCode Notebooks.
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kaggleやSIGNATEのようなデータ分析コンペでは時に大容量データを扱うことがあるので、ラップトップPCではメモリが足りなくなることがあります。そういう場合はつよつよPCを購入するかGCPやAWSのようなクラウド環境を利用するのですが、後者はプログラミング初心者には難しい面があります。Google CloudのAI Platform Notebooksを使うと簡単にコンペの分析環境を作れるため紹介したいと思います。 AI Platform Notebookのインスタンスを作成する Google Cloud Platformで新しいプロジェクトを作成する。(typoでpropjectになってしまいました) ナビゲーションメニュー > 人工知能 > AI Platform > ノートブック を選択する。 APIを有効にしていない場合は有効にする。 新しいインスタンスから好きな環境を選ぶ。
Visual Studio Code、「HexEditor拡張」「GitHub Issue Notebooks拡張」リモート開発など機能追加
Visual Studio Code、「HexEditor拡張」「GitHub Issue Notebooks拡張」リモート開発など機能追加：「June 2020」リリース Microsoftは、クロスプラットフォームエディタ「Visual Studio Code」の最新版「June 2020」リリース（バージョン1.47）を公開した。HexEditor拡張、GitHub Issue Notebooks拡張、リモート開発などの機能が強化されている。
GitHub - nlp-with-transformers/notebooks: Jupyter notebooks for the Natural Language Processing with Transformers book
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[GCP] AI Platform Notebooksが正式リリースされていたので使ってみる | DevelopersIO
こんにちは、Mr.Moです。 GCPのAI Platform Notebooksが先月末でGA（Generally Available：正式リリース）になりましたね！Google Colaboratoryも良いですが、こちらのサービスも気になるので早速使ってみます。 https://cloud.google.com/ai-platform/notebooks/docs/release-notes#March_31_2020 AI Platform Notebooksとは AI Platform Notebooks は、JupyterLab 統合開発環境を提供するマネージド サービスです。機械学習のデベロッパーとデータ サイエンティストは、最新のデータ サイエンスと機械学習のフレームワークがプリインストールされた JupyterLab を実行するインスタンスをワンクリックで作成できます。No
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A OneNote notebook is the main container for notes you capture within the app. It's like a specialized folder, but with its own interface and unique tools. You can put notes anywhere within a notebook, and sync them across your devices. Unfortunately, this simplicity of the notebook doesn't tell you how to use them properly. It's easy to wind up with a bookshelf full of notebooks. We'll show you h
Why we do machine learning engineering with YAML, not notebooks
Source: PexelsMost data scientists spend the majority of their working hours in a notebook. As a result, most production machine learning platforms prioritize notebook support. If you try out a new production ML platform, chances are its onboarding tutorial will begin with a .ipynb file. When we built Cortex, our production machine learning platform, we spent a lot of time considering the correct
GitHub - DonJayamanne/typescript-notebook: Run JavaScript and TypeScript in node.js within VS Code notebooks with excellent support for debugging, tensorflowjs visulizations, plotly, danfojs, etc
Enhanced REPL experience for Node.js in Notebooks (with top level awaits) Run & debug JavaScript, TypeScript code in node.js Built in support for typescript (ships with TypeScript & ts-node). Built in support for plotly (plotly.js is shipped with the extension) Rich (inline visualizations) using @tensorflow/tfjs-vis & Tensorboards Excellent support for danfo.js (rich HTML output and plots) Excelle
Netflix’s Polynote is a New Open Source Framework to Build Better Data Science Notebooks
Source: https://polynote.org/I recently started a new newsletter focus on AI education. TheSequence is a no-BS( meaning no hype, no news etc) AI-focused newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. Please give it a try by subscribing below:
GitHub - GoogleCloudPlatform/generative-ai: Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI
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GitHub - facebookresearch/sam2: The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
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GitHub - joouha/euporie: Jupyter notebooks in the terminal
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Jupyter notebooks are mostly known for their web-based user interface, such as JupyterLab or the Classic Notebook. They offer a great user experience, allow for rich output rendering, provide interactivity through e.g. widgets, and make possible working with remote kernels. If just like me you tend to never leave the terminal in your workflow, you may be missing a tool to interact with Jupyter not
GitHub - mlabonne/llm-course: Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
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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
GitHub - mljar/mercury: Convert Jupyter Notebooks to Web Apps
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[レポート] VS Code Day 2021 – NOTEBOOKS IN VS CODE ARE GETTING REVAMPED! – #VSCodeDay #VSCode #VisualStudioCode | DevelopersIO
[レポート] VS Code Day 2021 – NOTEBOOKS IN VS CODE ARE GETTING REVAMPED! – #VSCodeDay #VSCode #VisualStudioCode こんにちは、Mr.Moです。 初のVS Code公式カンファレンス 『VS Code Day 2021』が開催されましたね！? 本イベントではセッションがいくつか用意されていますが、本エントリーではそのうちの一つ『NOTEBOOKS IN VS CODE ARE GETTING REVAMPED!』をレポートしていきたいと思います。 VS Code Day 2021とは Join the Visual Studio Code team and community at a live event just for VS Code users. Get a glimpse of t
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GitHub - livebook-dev/livebook: Automate code & data workflows with interactive Elixir notebooks
Livebook is a web application for writing interactive and collaborative code notebooks. It features: Code notebooks with Markdown support and Code cells where Elixir code is evaluated on demand. Rich code editor through CodeMirror: with support for autocompletion, inline documentation, code formatting, etc. Interactive results via Kino: display Vega-Lite charts, tables, maps, and more. Automation:
The Python Extension for VS Code Insiders is excited to announce the new preview for Native Notebooks! Native Notebooks are VS Code’s newest implementation of notebooks and the Python Extension is leveraging the Native Notebooks API to revamp the data science experience! Users can now benefit from the new functionalities below: The same extensions that users rely on when editing source code or mar
GitHub - fastai/fastpages: An easy to use blogging platform, with enhanced support for Jupyter Notebooks.
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I blew $720 on 100 notebooks from Alibaba and started a Paper Website business | Tiny Projects
I blew $720 on 100 notebooks from Alibaba and started a Paper Website business December 14th 2021 TLDR; I started a business that lets you build websites using pen & paper. In the process I went viral on Twitter, made $1,000 in two days, and blew $720 on 100 paper notebooks from Alibaba. 📖 Can you build a website from a piece of paper? One day, a riddle popped into my brain: "Can you build a webs
GitHub - davidbrochart/nbterm: Jupyter Notebooks in the terminal.
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Deno’s mission is to dramatically simplify software development. In Deno 1.37, we’re happy to extend this to interactive Jupyter notebooks. Starting in 1.37, you can use the new deno jupyter command to create a Deno kernel that can be used within notebooks. Additionally, Deno 1.37 comes with stronger Visual Studio Code and LSP support, better testing performance, improved Node compatibility, and m
こんにちは！CREの池田です。ANDPAD Advent Calendar 18日目の本記事では、CREが業務で活用している Datadog Notebooks についてご紹介します。 Datadog Notebooksとは？ Datadog Notebooksは、Datadog内のログイベントやメトリクスをグラフ化し、ノート形式で整理・共有できるツールです。 使い始めたきっかけ CREでは、外形監視の一環としてDatadogを利用しており、今年から異常に重いリクエスト数の集計を自動化しました。この取り組みによって、重いリクエストのデータを効率的に集められるようになりました。 次のステップとして、どのリクエストを優先して改善していくべきかを見極めてPMへ連携する必要がありますが、各リクエストに対して調査から共有のための下準備が手間だという課題がありました。 今回は、Datadog Note
GitHub - jupyterlab/debugger: A visual debugger for Jupyter notebooks, consoles, and source files
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アップデートされたAzure Machine Learning Studio Notebooksは何ができるのかを確認してみる #Azure #AzureMachineLearning | DevelopersIO
こんにちは、Mr.Moです。 先日、Azure Machine Learning StudioのWeb experienceが一般提供開始(GA)されましたね。それに合わせてAzure Machine Learning Studio の Notebooks もアップデートが入っていますので現状を確認していきたいと思います。 Azure Machine Learning Studio Notebooks とは 本日、Azure Machine Learning Studioのノートブックエディタの機能強化版がリリースされました。このアップデートにより、Azure ML ワークスペースのメンバーは、自分たちの ML 実験、メトリクス、モデル、データセットなどを含む同じ環境でノートブックの編集、共有、コラボレーションが可能になります。新しいStudio Notebooksを使えば、データサイエン
GitHub - fonsp/Pluto.jl: 🎈 Simple reactive notebooks for Julia
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GitHub - dotnet/interactive: .NET Interactive combines the power of .NET with many other languages to create notebooks, REPLs, and embedded coding experiences. Share code, explore data, write, and learn across your apps in ways you couldn't before.
Since .NET Interactive is capable of running as a kernel for notebooks, it enables a polyglot (multi-language) notebook experience. When using the .NET Interactive kernel, you can use different languages from one cell to the next, share variables between languages, and dynamically connect new languages and remote kernels within a notebook. There's no need to install different Jupyter kernels, use
“Conway’s Gradient of Life” という記事に、ライフゲームを逆算する手法について書かれており、面白かったので私も自分で試してみることにしました。ライフゲームは、セル・オートマトンと呼ばれる2次元のグリッド上で動作するシミュレーションで、各セルは隣接するセルの状態に応じて次のステップでの生死の状態が決定します。ライフゲームを「逆算する」とは、ある特定のパターンに至る前の状態を推定することを意味します。つまり、1ステップ進めるとある形に収束する状態を、その形から逆に探し出す課題です。 今回は、ライフゲームのルールに基づいて1ステップ進めた時に、私のアイコンが現れるような初期状態を求めてみたいと思います。このテーマは以前、Kaggleのコンペでも扱われていたことがあったり、調べてみるといくつかのアプローチが存在します。例えば、焼きなまし法を用いたもの、遺伝的アルゴリズムを
Dive deep into Amazon SageMaker Studio Classis Notebooks architecture | Amazon Web Services
AWS Machine Learning Blog Dive deep into Amazon SageMaker Studio Classis Notebooks architecture NOTE: Amazon SageMaker Studio and Amazon SageMaker Studio Classic are two of the machine learning environments that you can use to interact with SageMaker. If your domain was created after November 30, 2023, Studio is your default experience. If your domain was created before November 30, 2023, Amazon S
GitHub - karolzak/ipyplot: IPyPlot is a small python package offering fast and efficient plotting of images inside Python Notebooks. It's using IPython with HTML for faster, richer and more interactive way of displaying big numbers of images.
Share: IPyPlot is a small python package offering fast and efficient plotting of images inside Python Notebooks cells. It's using IPython with HTML for faster, richer and more interactive way of displaying big numbers of images. Displaying big numbers of images with Python in Notebooks always was a big pain for me as I always used matplotlib for that task and never have I even considered if it can
January 15, 2025 · 4 mins · 762 words I’ve been using LLM-assisted coding for the last couple of months, and it has been a game-changer. After a couple of iterations, my setup consists in ContinueDev + OpenRouter. I’m using OpenRouter because I can access all the models I need from a single provider and control my budget from a single entry point. Use Sonnet 3.6 for “easy” questions or edits, and
Polyglot Notebooks - Visual Studio Marketplace
Features Run and execute code for all featured languages Share variables between languages Connect to and query Microsoft SQL Server Connect to and query Kusto clusters Language server support such as completions, syntax highlighting, signature help, and diagnostics for each language See the state of all variables using the Variables View Create detailed diagrams and visualizations using Mermaid I
GitHub - facebookresearch/segment-anything: The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
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GitHub - anthropics/anthropic-cookbook: A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
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GitHub - tugstugi/dl-colab-notebooks: Try out deep learning models online on Google Colab
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Google CloudのAI Platform Notebooksで楽々コンペ環境の構築 - Qiita
How to Organize Notebooks With OneNote
nbterm: Jupyter Notebooks in the terminal
Python Jupyter Notebooks in Excel
Notebooks are getting revamped! - Python
Deno 1.37: Modern JavaScript in Jupyter Notebooks
Datadog Notebooksを活用した重いリクエスト調査の改善 - ANDPAD Tech Blog
微分可能な比較演算子でライフゲームを逆算する – lotz’s Haskell notebooks
Optimizing Jupyter Notebooks for LLMs
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