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Based on our record, Jupyter seems to be a lot more popular than Coresignal. While we know about 216 links to Jupyter, we've tracked only 1 mention of Coresignal. 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 wasnโt designed in isolation โ it was built in the data pipeline world, where every data engineerโs 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 โ 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, OpenAIโs 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
Solo founder here looking for some input and feedback from the HN community. I'm building a SaaS to help with discovering and researching businesses. So far I have information on about 1M US companies, including URL, name, description, associated stock symbol, etc etc. This could of course support different workflows for a number of possible ICPs. I'm working with one person in private equity now to do geographic... - Source: Hacker News / about 1 month ago
Looker - Looker makes it easy for analysts to create and curate custom data experiencesโso everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
People Data Labs - Use our dataset of 1.5 billion unique person profiles to build products, enrich person profiles, power predictive modeling/AI, analysis, and more. We work with technical teams as their engineering focused people data partner.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
TheirStack - Find companies by the technology they use
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.โWhat is Apache Spark?
Bright Data - World's largest proxy service with a residential proxy network of 72M IPs worldwide and proxy management interface for zero coding.