Based on our record, Jupyter seems to be a lot more popular than Inoreader. While we know about 216 links to Jupyter, we've tracked only 14 mentions of Inoreader. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Were can I set in inoreader.com settings so that the articles opens in normal web browser tab and not the light version of the article? Ive been checking the settings but cannot find any settings to change this. (Feedly calls this option "open in website directly"). Source: almost 2 years ago
As an alternative, you can use Feedbro or Inoreader. Source: about 2 years ago
I've Inoreader subscription for several years. It is not specific to Mac, though. But it has been particularly valuable for me with their server-side filters and deduplication. Recently, they added Newsletter subscriptions and website subscriptions for sites which don't offer RSS feeds. Pretty nifty if you need them. Source: about 2 years ago
Was using Feedly but it stopped working a couple years ago. Now I use inoreader - it has a nice interface on both web and in the app, and you can follow more than just RSS (customizable keyword searches) in the paid version. Source: about 2 years ago
No ability to customize font-size, and it's waaaaay too big for me on all platforms. This results in tons more scrolling that what's needed with Raindrop and Inoreader <-- major dealbreaker for me. Source: over 2 years ago
Showcase and share: Easily embed UIs in Jupyter Notebook, Google Colab or share them on Hugging Face using a public link. - Source: dev.to / 3 months ago
LangChain wasn’t designed in isolation — it was built in the data pipeline world, where every data engineer’s tool of choice was Jupyter Notebooks. Jupyter was an innovative tool, making pipeline programming easy to experiment with, iterate on, and debug. It was a perfect fit for machine learning workflows, where you preprocess data, train models, analyze outputs, and fine-tune parameters — all in a structured,... - Source: dev.to / 4 months ago
Leverage versatile resources to prototype and refine your ideas, such as Jupyter Notebooks for rapid iterations, Google Colabs for cloud-based experimentation, OpenAI’s API Playground for testing and fine-tuning prompts, and Anthropic's Prompt Engineering Library for inspiration and guidance on advanced prompting techniques. For frontend experimentation, tools like v0 are invaluable, providing a seamless way to... - Source: dev.to / 5 months ago
Lately I've been working on Langgraph4J which is a Java implementation of the more famous Langgraph.js which is a Javascript library used to create agent and multi-agent workflows by Langchain. Interesting note is that [Langchain.js] uses Javascript Jupyter notebooks powered by a DENO Jupiter Kernel to implement and document How-Tos. So, I faced a dilemma on how to use (or possibly simulate) the same approach in... - Source: dev.to / 9 months ago
One of the most convenient ways to play with datasets is to utilize Jupyter. If you are not familiar with this tool, do not worry. I will show how to use it to solve our problem. For local experiments, I like to use DataSpell by JetBrains, but there are services available online and for free. One of the most well-known services among data scientists is Kaggle. However, their notebooks don't allow you to make... - Source: dev.to / 12 months ago
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