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
- 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
Python open source libraries for scaling time series forecasting solutions
By Francesca Lazzeri. This article is an extract from the book Machine Learning for Time Series Forecasting with Python, also by Lazzeri, published by Wiley. In the first and second articles in this series, I showed how to perform feature engineering on time series data with Python and how to automate the Machine Learning lifecycle for time series forecasting. In this third and concluding article,
Join a VS Code Dev Days event near you to learn about AI-assisted development in VS Code. Update 1.70.1: The update addresses these issues. Update 1.70.2: The update addresses these issues. Update 1.70.3: This update is only available for Windows 7 users and is the last release supporting Windows 7. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welc
Using the Python Interactive window The Python Interactive window, mentioned in the previous section, can be used as a standalone console with arbitrary code (with or without code cells). To use the window as a console, open it with the Jupyter: Create Interactive Window command from the Command Palette. You can then type in code, using Enter to go to a new line and Shift+Enter to run the code. To
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
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
GitHub - marimo-team/marimo: A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. All in a modern, AI-native editor.
A reactive Python notebook that's reproducible, git-friendly, and deployable as scripts or apps. Docs · Discord · Examples · Gallery · YouTube English | 繁體中文 | 简体中文 | 日本語 | Español marimo is a reactive Python notebook: run a cell or interact with a UI element, and marimo automatically runs dependent cells (or marks them as stale), keeping code and outputs consistent. marimo notebooks are stored as
Identifying training bottlenecks and system resource under-utilization with Amazon SageMaker Debugger | Amazon Web Services
Artificial Intelligence Identifying training bottlenecks and system resource under-utilization with Amazon SageMaker Debugger At AWS re:Invent 2020, AWS released the profiling functionality for Amazon SageMaker Debugger. In this post, we expand on the importance of profiling deep neural network (DNN) training, review some of the common performance bottlenecks you might encounter, and demonstrate h
marimo
Developer experience is core to marimo, with an emphasis on reproducibility, maintainability, composability, and shareability. Highlights¶ 🚀 batteries-included: replaces jupyter, streamlit, jupytext, ipywidgets, papermill, and more ⚡️ reactive: run a cell, and marimo reactively runs all dependent cells or marks them as stale 🖐️ interactive: bind sliders, tables, plots, and more to Python — no ca
GitHub - taishi-i/awesome-ChatGPT-repositories: A curated list of resources dedicated to open source GitHub repositories related to ChatGPT and OpenAI API
awesome-chatgpt-api - Curated list of apps and tools that not only use the new ChatGPT API, but also allow users to configure their own API keys, enabling free and on-demand usage of their own quota. awesome-chatgpt-prompts - This repo includes ChatGPT prompt curation to use ChatGPT better. awesome-chatgpt - Curated list of awesome tools, demos, docs for ChatGPT and GPT-3 awesome-totally-open-chat
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
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Rustでグラフをplotするライブラリのまとめ - Stimulator
July 2022 (version 1.70)
Python Interactive window
Python Jupyter Notebooks in Excel
Why We Use Julia, 10 Years Later