Maven
GoIT LMS
Mini Course Generator
CMake
GNU Make
Graphy
Udemy
Teachify
Deepnote
Apache Zeppelin
Saturn Cloud
Amazon SageMaker
Databricks Unified Analytics Platform
Azure Synapse Analytics
Google BigQuery
GeoSpock
Maven is recommended for healthcare providers, insurance companies, and employers looking to integrate digital health solutions into their offerings. It is also ideal for patients seeking convenient access to healthcare professionals and services online.
Based on our record, Deepnote should be more popular than Maven. It has been mentiond 34 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.
Maven (https://maven.com) | Senior Software Engineer (Full-stack, product) | US, Canada Remote | $160-200k About us: building the university of the future, starting with the largest marketplace of expert-led cohort-based-courses on the Internet. We're a 5 person eng team and a 15 person team led by the founders of Udemy, Venmo, Socratic. Raised $25 million from a16z and First Round in 2021, have 3+ years of... - Source: Hacker News / almost 3 years ago
Have any of your tried learning from this cohort based e-learning platform - https://maven.com/? Source: about 3 years ago
Maven | Remote (within 1 hour of US timezones) | https://maven.com/ Maven is building the university of the future - empowering the world’s experts to offer live courses directly to their students. We're the leading marketplace for cohort-based courses. Maven is a startup funded by First Round Capital, a16z, and others. We are hiring for:- Source: Hacker News / over 3 years ago- Senior full-stack engineer.
In other news: I joined the maven.com course accelerator to build a cohort-based course with the title From Jargon to Clarity - Navigating Different Audiences in Tech. - Source: dev.to / over 3 years ago
Thank you for the list - I think I've come across all of these in my research! I'll try highlight the differences for each. - https://noteable.io/ - as you say, it doesn't exist anymore - https://deepnote.com - I actually mentioned this in the post but in my experience, the UX and features far behind what we've built already. I'd love to hear from anyone who's tried jupyter-ai to give us a shot and let me know... - Source: Hacker News / about 2 years ago
- https://deepnote.com -- also extensive AI integration and realtime collaboration. - Source: Hacker News / about 2 years ago
Deepnote - A new data science notebook. Jupyter is compatible with real-time collaboration and running in the cloud. The free tier includes unlimited personal projects, up to 750 hours of standard hardware, and teams with up to 3 editors. - Source: dev.to / over 2 years ago
We looked into many of these issues with Deepnote (YC S19) [https://deepnote.com/]. What we found is that these are not necessarily problems of the underlying medium (a notebook), but more of the specific implementation (Jupyter). We've seen a lot of progress in the Jupyter ecosystem, but unfortunately almost none in the areas you mentioned. - Source: Hacker News / about 3 years ago
Upload your ipynb to Deepnote and publish as an app. That simple. https://deepnote.com. - Source: Hacker News / over 3 years ago
GoIT LMS - Empowering emerging markets with high-quality tech education
Apache Zeppelin - A web-based notebook that enables interactive data analytics.
Mini Course Generator - Mini Course Generator is the easiest way to create and deliver mini-courses & micro-learning materials. Save time with the AI Course Creator.
Saturn Cloud - ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.
CMake - CMake is an open-source, cross-platform family of tools designed to build, test and package software.
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.