AWS Lambda might be a bit more popular than Jupyter. We know about 277 links to it since March 2021 and only 216 links to Jupyter. 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 / 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
In this tutorial, you will walk through the process of building, testing, and deploying a multi-agent AI system using LangGraph, Docker, AWS Lambda, and CircleCI. You will develop a research-driven AI workflow where different agents,such as fact-checking, summarization, and search agents, work together seamlessly. You will package this application into a Docker container, deploy it to AWS Lambda, and automate the... - Source: dev.to / 10 days ago
Teachers, freelancers, and inbox zero purists rejoice: I built EmailDrop, a one-click AWS deployment that turns incoming emails into automatic Google Drive uploads. With Postmark's new inbound webhooks, AWS Lambda, and a little OAuth wizardry, attachments fly straight from your inbox to your Google Drive. In this post, I’ll walk through how I built it using Postmark, CloudFormation, Google Drive, and serverless... - Source: dev.to / 16 days ago
Serverless architectures are revolutionizing software development by removing the need for server management. Cloud services like AWS Lambda, Google Cloud Functions, and Azure Functions allow developers to concentrate on writing code, as these platforms handle scaling automatically. - Source: dev.to / 26 days ago
In this application, we will create products and retrieve them by their ID and use Amazon DynamoDB as a NoSQL database for the persistence layer. We use Amazon API Gateway which makes it easy for developers to create, publish, maintain, monitor and secure APIs and AWS Lambda to execute code without the need to provision or manage servers. We also use AWS SAM, which provides a short syntax optimised for defining... - Source: dev.to / about 1 month ago
AWS CloudFront is the star of the show here. It caches static content (like media, scripts, and images) to ensure fast, reliable delivery. Other AWS services that run at the edge include Route 53 for DNS routing, Shield and WAF for security, and even Lambda via Lambda@Edge — giving you the ability to run serverless logic closer to the user. - Source: dev.to / about 1 month ago
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
Amazon API Gateway - Create, publish, maintain, monitor, and secure APIs at any scale
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Google App Engine - A powerful platform to build web and mobile apps that scale automatically.