Based on our record, Jupyter should be more popular than Feedly. It has been mentiond 216 times since March 2021. 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.
Feedly [0] (web app and on IOS) has been amazing since Google Reader died. On IOS it makes flipping through items and saving them for later a smooth and relatively fast experience. [0] https://feedly.com. - Source: Hacker News / 9 months ago
With the introduction of my blogroll, my morning routine has changed without me having planned it. By displaying the latest blogger posts there by fetsching them while the site is build once a day, I start reading there instead of in my standard feed reader feedly. I no longer subscribe to the 40 blogs currently on my list, but use Read You as a blogroll reader in case I miss something. - Source: dev.to / 10 months ago
Some people enjoy sharing their knowledge on technical areas, blogs remain accessible and effective media. Feedly or Inoreader will allow you to follow the RSS feeds of these websites and consult them at your leisure, so you can follow the specific areas that interest you. - Source: dev.to / about 1 year ago
Maybe not a perfect replacement, but have you tried Feedly? https://feedly.com/. - Source: Hacker News / over 1 year ago
Pretty sure Feedly is the most popular news aggregator these days. I've been using it for years, and it is great. https://feedly.com/. - Source: Hacker News / almost 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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