Jupyter VS A-mates
Compare Jupyter VS A-mates and see what are their differences
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A-mates is a powerful and cost-efficient solution that allows you to integrate a community section resembling a forum into your mobile application. By seamlessly incorporating our SDK into your iOS or Android app, customizing it within seconds, placing an entrance button wherever you prefer, your very own community will be set up and ready to go!
Improve user engagement, foster customer loyalty, and take your customer development to the next level! Our free forever version gives you the freedom to explore A-mates at your own pace. For unlimited functionality, our subscription is priced at just $299 per month. Additionally, we have attractive offers specifically tailored for startups – feel free to inquire about them.
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A-mates's answer:
A-mates is a product from Orangesoft, a mobile app developer. In response to numerous customer requests for custom in-app community development, we introduced the "Community SDK," a more cost-effective solution. Eventually, we combined the SDK, backend, and community management panel into one cohesive product - A-mates. We take pride in the fact that our product was born out of the genuine needs of mobile app owners, and we remain committed to providing the finest in-app community service possible.
A-mates's answer:
A-mates is the only product in the market that offers a forum-like in-app community, distinct from social networks or "embedded Instagram". It provides users with the ability to post, read, and react to topics and comments through threaded discussions. It's as simple as that.
A-mates's answer:
Our goal is to provide a convenient and efficient communication tool for all iOS and Android apps. Therefore, any mobile app with over 1k installations is eligible to be our customer. BTW, we provide a free forever plan that can help mobile startups to begin receiving the advantages of an in-app community at no cost.
A-mates's answer:
Distinguishing itself from other mobile social tools providers, A-mates stands out with its transparent flat pricing of $299 per month. Unlike competitors that tie pricing to monthly active users (MAU) or other metrics, A-mates guarantees the provision of an in-app community for your mobile app, regardless of whether you have 1,000 or 300,000 MAU.
We've been working with the a-mates community for over four months now. Our goal was to create a platform similar to Reddit, where our users can interact within the app. The forum-style structure offered by a-mates was exactly what we needed. Although we encountered a few minor challenges initially, the a-mates support team promptly resolved them. Therefore, we highly recommend a-mates as an excellent provider of community-as-a-service for mobile apps!
Based on our record, Jupyter seems to be more popular. 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.
Showcase and share: Easily embed UIs in Jupyter Notebook, Google Colab or share them on Hugging Face using a public link. - Source: dev.to / 7 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 / 8 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 / 9 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 / about 1 year 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 / over 1 year ago
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