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Which is more popular?
Based on our record, 17Lands Client
should be more popular than Deepnote.
It has been mentioned 82 times since March 2021.
social mentions
34 vs 82
Data Science And Machine Learning popularity
100% vs 0%
alternatives listed
111 vs 6
Base details
Website, pricing, platforms and company facts side by side.
Collaborative Features Deepnote allows for real-time collaboration, similar to Google Docs, where multiple users can work on the same notebook simultaneously without conflicts.
Integration with Popular Tools Deepnote integrates seamlessly with popular data sources and tools such as Google Drive, GitHub, and SQL databases, enhancing its versatility for data science projects.
User-Friendly Interface The interface is clean and easy to navigate, making it accessible for both beginners and experienced data scientists.
Cloud-Based Being a cloud-based solution, Deepnote eliminates the need for local setup and maintenance, allowing users to access their projects from anywhere with internet access.
Data Security Deepnote provides robust security features, ensuring that your data and notebooks are protected against unauthorized access.
Integrated Version Control Version control within Deepnote allows users to track changes, revert to previous versions, and collaborate more effectively on shared projects.
Possible disadvantages
Limited Offline Access As a cloud-based platform, Deepnote requires an internet connection for most of its functionality, which can be a limitation for users needing offline access.
Performance Constraints Heavy computational tasks might be limited by the performance capabilities of the cloud resources provided, affecting users who require extensive computational power.
Subscription Costs While there is a free tier, advanced features and increased resource limits come at a subscription cost, which might be a consideration for students or hobbyists.
Learning Curve for Advanced Features While basic functionality is user-friendly, mastering the more advanced features and integrations may require a learning curve, especially for users new to data science tools.
Dependency on External Infrastructure The performance and availability of Deepnote can be affected by issues with their cloud service providers, which adds a layer of dependency on external infrastructure.
Data-Driven Insights 17Lands provides detailed analytics and statistics that help Magic: The Gathering players make informed decisions about card selection and deck building.
User-Friendly Interface The client offers a clean and intuitive interface, making it easy for users to navigate through data and find the information they need.
Draft Improvement By analyzing win rates and other performance metrics, players can improve their draft skills and overall gameplay.
Community Support 17Lands has a supportive community of users and developers who frequently share tips and insights, contributing to a collaborative learning environment.
Regular Updates The platform is regularly updated with new features and data to stay current with the latest Magic: The Gathering sets and trends.
Possible disadvantages
Limited to Arena The 17Lands client primarily supports Magic: The Gathering Arena, so players of the physical card game or other digital platforms might find it less useful.
Data Overload For new users, the sheer amount of data and statistics can be overwhelming, requiring time to familiarize themselves with its utility.
Requires Consistent Use To get the most out of 17Lands, users need to consistently upload and review their game data, which can be time-consuming.
Privacy Concerns Sharing game data might raise privacy concerns for some users, as it involves linking their gaming account with the 17Lands client.
Potential for Over-reliance Players might become overly reliant on the tool's recommendations and lose the creative aspect of personal strategy development.
Analysis
An editorial look at what each product does well and who it suits.
Deepnote17Lands Client
Overall verdict
Deepnote is an excellent tool for data scientists, particularly those who value collaboration and need interactive, shareable notebooks. Its user-friendly interface and powerful integration capabilities make it a strong contender in the data science notebook space.
Why this product is good
Deepnote is a collaborative data science notebook designed to enhance productivity and simplify the data science workflow. It offers real-time collaboration, similar to Google Docs, making it easier for teams to work together efficiently. It supports various programming languages and integrates seamlessly with popular tools such as Jupyter notebooks, Git, and cloud storage services. Deepnote also provides a strong focus on data visualization and interactive dashboards, making it easier to interpret and present data insights.
Recommended for
Data scientists who work in teams and need a collaborative environment.
Professionals who require seamless integration with existing tools and cloud storage.
Users who prioritize interactive data visualization and interpretability.
Educators looking for an accessible platform to teach data science concepts.
Deepnote is a cloud-based data science notebook platform comparable to Jupyter Notebooks but with a focus on real-time collaboration and editing. It lets users write and run code in several programming languages, as...
Deepnote is a real-time collaborative notebook. It offers features like real-time collaboration, version control, and smart autocomplete. It also provides direct integrations with popular data sources like GitHub,...
Deepnote is a cloud-based, data science notebook platform that is similar to Jupyter Notebooks, but with a focus on collaboration and real-time editing. It allows users to write and execute code in a variety of...
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...
- Source: Hacker News
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over 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
/
almost 3 years ago
Getting an average of 2-3 wins in Quick Draft is fairly decent for a new drafter. If you think you're learning at all, it's worth sticking with it to get better. You should be able to learn the fastest when you're starting out. In...
Source:
over 3 years ago
Where did I go wrong?
The best thing to identify the best cards from fillers and bad cards is watcing the win rate stats in 17lands.com.
Source:
over 3 years ago
Ask r/Spikes || May 2023
17lands.com has huge amount of data on every limited format that is available on Arena.
Source:
over 3 years ago
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.
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