Software Alternatives & Reviews

Call to Idea VS Papers with Code

Compare Call to Idea VS Papers with Code and see what are their differences


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Call to Idea Landing Page
Call to Idea Landing Page
Papers with Code Landing Page
Papers with Code Landing Page

Call to Idea details

Categories
Tech User Experience Web App Design Tools
Website calltoidea.com  

Papers with Code details

Categories
Email Deliverability Cold Outreach Artificial Intelligence
Website paperswithcode.com  

Call to Idea videos

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Papers with Code videos

The best site for research papers with codes on Machine/Deep Learning | Research paper search

More videos:

  • - Papers With Code Machine Learning Papers and Code Free Resource

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Social recommendations and mentions

Based on our record, Papers with Code seems to be more popular. It has been mentiond 24 times since March 2021. We are tracking product recommendations and mentions on Reddit, HackerNews and some other platforms. They can help you identify which product is more popular and what people think of it.

Call to Idea mentions (0)

We have not tracked any mentions of Call to Idea yet. Tracking of Call to Idea recommendations started around Mar 2021.

Papers with Code mentions (24)

  • [Newcomer] Status of AI, graphics programming and performance in Haskell?
    Interesting! I guess we could help populate Papers with Code and hope others appreciate functional programming like we do! (If no one is willing, I'll after I become proefficient enough!). - Source: Reddit / 23 days ago
  • PyTorch 1.10
    Really depends on where you are coming from. If you are already working in Deep Learning, and super comfortable in some other framework, then- -> Head over to the PyTorch website, and go through the introductory tutorials. -> Go to Papers with Code [0], and start reading and trying out implementing relatively easier research papers. If you are a beginner, then, you can go through resources that reach Deep Learning... - Source: Hacker News / about 1 month ago
  • Which book do you recommend to go deeper into Deep Learning?
    As far as more practical stuff goes, if all you want is more time spent actually coding and using a library (vs building up a deeper theoretical understanding) then just get rolling with implementing some papers to start. There's all kinds of really cool directions you can go... Pick a problem and implement a few different important historical landmarks. On papers with code it's pretty easy to find a problem... - Source: Reddit / about 1 month ago
  • Example models
    There is the website paperswithcode. This website compile paper and their implementation on github. So you look at a loooot of Pytorch repository. - Source: Reddit / about 1 month ago
  • Tutorials for creating LSTM from scratch?
    You'll usually see RNNs in language modeling, time series forecasting, etc., while CNNs come up a lot in image recognition and other computer vision tasks. A good resource is Papers with Code (https://paperswithcode.com). They have some pages on methods, so you can see where RNNs and CNNs have been used in papers over the past 20 or so years:. - Source: Reddit / 2 months ago
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What are some alternatives?

When comparing Call to Idea and Papers with Code, you can also consider the following products

Curator - The visual notes app, now on iPhone!

ML5.js - Friendly machine learning for the web

MakeML - Train Neural Networks without a line of code

Machine Learning Weekly - A hand-picked newsletter in machine learning & deep learning

appealing - Mobile UI animations found in the wild

Amazon Machine Learning - Machine learning made easy for developers of any skill level

User reviews

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