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,
In Praise of dhh
In Praise of dhh November 8, 2025 | #tech #politics A reflection on Ruby’s past, present, and future. This is a long essay. I strongly recommend you read it from the beginning, but to help navigate it I have created this table of contents. Prologue The Past How I Learned To Love Ruby A Breath Of Fresh Air A Shared Worldview The Present Tragedy Strikes Recent Conflict In The Community Strength and
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
leafmap
Home Home Book Installation Get Started Usage Web App Tutorials Contributing FAQ Changelog YouTube Channel Report Issues API Reference Workshops Notebooks Welcome to leafmap¶ A Python package for geospatial analysis and interactive mapping in a Jupyter environment. GitHub repo: https://github.com/opengeos/leafmap Documentation: https://leafmap.org PyPI: https://pypi.org/project/leafmap Conda-forge
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
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
Visualisation Libraries - JavaScript, Python and More
The libraries and toolkits discussed in this article can be used for rendering dynamic plot on desktop, mobile and web-based platforms so that a quick summary of results can be presented. These tools can be used by data scientists and researchers for an effective analysis of dynamic data. But, before moving on to these tools/libraries, let's look at some obvious points! The key features and charac
Julia 1.0 came out well over 2 years ago. Since then a lot has changed and a lot hasn’t. Julia 1.0 was a commitment to no breaking changes, but that is not to say no new features have been added to the language. Julia 1.6 is a huge release and it is coming out relatively soon. RC-1 was released recently. I suspect we have at least a few more weeks before the final release. The Julia Core team take
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
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
Sean Moriarity and I are glad to announce that the project we have been working on for the last 3 months, Nx, is finally publicly available on GitHub. Our goal with Nx is to provide the foundation for Numerical Elixir. In this blog post, I am going to outline the work we have done so far, some of the design decisions, and what we are planning to explore next. If you are looking for other resources
This article will discuss the Matplotlib library,” in the data scientist’s toolbox on Python. Matplotlib is a library very commonly used by data scientists…. In addition to “Matplotlib,” “Pandas,” and “NumPy” are important parts of the data scientist’s toolbox. Introduction to MatplotlibIs it possible to know your data’s trend or pattern without visualization? In my view, the answer is definitely
GitHub - ComfyUI-Workflow/awesome-comfyui: A collection of awesome custom nodes for ComfyUI
ComfyUI-Gemini_Flash_2.0_Exp (⭐+172): A ComfyUI custom node that integrates Google's Gemini Flash 2.0 Experimental model, enabling multimodal analysis of text, images, video frames, and audio directly within ComfyUI workflows. ComfyUI-ACE_Plus (⭐+115): Custom nodes for various visual generation and editing tasks using ACE_Plus FFT Model. ComfyUI-Manager (⭐+113): ComfyUI-Manager itself is also a cu
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Python Jupyter Notebooks in Excel
Why We Use Julia, 10 Years Later
Julia 1.6: what has changed since Julia 1.0?
Nx (Numerical Elixir) is now publicly available - Dashbit Blog
Fundamentals of Matplotlib Library for Data Science