Software Alternatives, Accelerators & Startups

Elmeasure VS Deep playground

Compare Elmeasure VS Deep playground and see what are their differences

Elmeasure logo Elmeasure

Elmeasure India / Elecon Measurements - Empowers you to Manage Power - Elmeasure Offers Energy management Software / Energy Monitoring System / Energy Monitoring Solutions - (EMS /SCADA) ,Demand Controller, Multi-Function Meter,Load Manager,Electron…

Deep playground logo Deep playground

Deep playground is an interactive visualization of neural networks, written in typescript using d3.
  • Elmeasure Landing page
    Landing page //
    2023-03-15
  • Deep playground Landing page
    Landing page //
    2019-09-01

Elmeasure videos

Elmeasure MultiFuction Meter

More videos:

  • Review - Training on ELMEASURE iACCL
  • Review - Elmeasure Product Basket - Digital Panel Meters

Deep playground videos

No Deep playground videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Elmeasure and Deep playground)
Energy And Utilities Vertical Software
Simulation
0 0%
100% 100
Project Management
100 100%
0% 0
Spreadsheets
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Deep playground seems to be more popular. It has been mentiond 26 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.

Elmeasure mentions (0)

We have not tracked any mentions of Elmeasure yet. Tracking of Elmeasure recommendations started around Mar 2021.

Deep playground mentions (26)

  • Why do tree-based models still outperform deep learning on tabular data? (2022)
    Not the parent, but NNs typically work better when you can't linearize your data. For classification, that means a space in which hyperplanes separate classes, and for regression a space in which a linear approximation is good. For example, take the circle dataset here: https://playground.tensorflow.org That doesn't look immediately linearly separable, but since it is 2D we have the insight that parameterizing by... - Source: Hacker News / 3 months ago
  • Introduction to TensorFlow for Deep Learning
    For visualisation and some fun: http://playground.tensorflow.org/. - Source: dev.to / 6 months ago
  • Visualization of Common Algorithms
    Https://seeing-theory.brown.edu/ https://www.3blue1brown.com/ https://playground.tensorflow.org/. - Source: Hacker News / 10 months ago
  • Stanford A.I. Courses
    There’s an interactive neural network you can train here, which can give some intuition on wider vs larger networks: https://mlu-explain.github.io/neural-networks/ See also here: http://playground.tensorflow.org/. - Source: Hacker News / 12 months ago
  • Let's revolutionize the CPU together!
    This site is worth playing around with to get a feel for neural networks, and somewhat about ML in general. There are lots of strategies for statistical learning, and neural nets are only one of them, but they essentially always boil down into figuring out how to build a “classifier”, to try to classify data points into whatever category they best belong in. Source: 12 months ago
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What are some alternatives?

When comparing Elmeasure and Deep playground, you can also consider the following products

SoFi - Easy Investing For Smart People. Modern investment management.

Neuronify - An educational neural network app.

Copper Tree Analytics - CopperTree's Kaizen software helps our clients take greater control of their buildings through powerful energy analytics, virtual metering and automated Fault Detection and Diagnostics (FDD), resulting in time and resource savings for facility manag…

Netron - Open-source visualizer for neural network, deep learning and machine learning models.

NTS Utility Billing - NTS Utility Billing solution offers for all your utility billing software needs.

Neural Designer - Neural Designer is a high performance data science and machine learning platform.