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Neural Networks and Deep Learning VS Weights & Biases

Compare Neural Networks and Deep Learning VS Weights & Biases and see what are their differences

GEES
GEES is an all-in-one AI design platform that is shaping a future where you can brainstorm, design, hand-off in one file — without changing any other tools. featured
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Neural Networks and Deep Learning logo Neural Networks and Deep Learning

Core concepts behind neural networks and deep learning

Weights & Biases logo Weights & Biases

Developer tools for deep learning research
  • Neural Networks and Deep Learning Landing page
    Landing page //
    2021-07-27
  • Weights & Biases Landing page
    Landing page //
    2023-07-24

Category Popularity

0-100% (relative to Neural Networks and Deep Learning and Weights & Biases)

Neural Networks and Deep Learning

Weights & Biases

AI
57 57%
AI
43% 43
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Developer Tools
47 47%
Developer Tools
53% 53
Data Science Notebooks
0 0%
Data Science Notebooks
100% 100

User comments

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Social recommendations and mentions

Based on our record, Neural Networks and Deep Learning seems to be more popular. It has been mentiond 44 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.

Neural Networks and Deep Learning mentions (44)

  • How do I begin building AI tools for myself?
    For neural network theory, I'm very fond of http://neuralnetworksanddeeplearning.com, but you'll need calculus and some linear algebra to understand it. Source: 5 months ago
  • What would be a project oriented roadmap to learn ML, deep learning (assuming I know Python and the required math - calculus, linear algebra and stats)?
    Alternatively, building them from scratch in numpy is definitely possible and an excellent way to learn the fundamentals. It will take some time though (debugging issues with a hand-rolled LSTM is very, very painful). There's a zillion tutorials/books out there (I think I started with http://neuralnetworksanddeeplearning.com). Source: 5 months ago
  • Ask HN: In 2023 which is the best path to learn machine and deep learning?
    - http://neuralnetworksanddeeplearning.com/ The Watch the Caltech telecourse. - Source: Hacker News / 8 months ago
  • Ask HN: What books or courses do you know similar to "From Nand to Tetris"?
    Neural Networks and Deep Learning, a free online book. http://neuralnetworksanddeeplearning.com/. - Source: Hacker News / 9 months ago
  • Why Do ML on the Erlang VM?
    Many years ago I was studying deep learning using this resource: * http://neuralnetworksanddeeplearning.com/ I decided to try to implement everything from scratch in Elixir (after initially doing all the math with pen and paper on a trivial example to get the feel of it). Obviously pure elixir was extremely slow, so I started creating NIFs to pass over matrix multiplication to OpenBLAS. Then I was thinking more... - Source: Hacker News / 11 months ago
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Weights & Biases mentions (0)

We have not tracked any mentions of Weights & Biases yet. Tracking of Weights & Biases recommendations started around Mar 2021.

What are some alternatives?

When comparing Neural Networks and Deep Learning and Weights & Biases, you can also consider the following products

Colornet - Neural Network to colorize grayscale images

neptune.ai - Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.

Quick Draw Game - Can a neural network learn to recognize doodles?

Algorithmia - Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.

AETROS - Create, train and monitor deep neural networks

Managed MLflow - Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.

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