Software Alternatives, Accelerators & Startups

Deep playground VS @RISK

Compare Deep playground VS @RISK and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Deep playground logo Deep playground

Deep playground is an interactive visualization of neural networks, written in typescript using d3.

@RISK logo @RISK

@RISK is the world's most widely used risk analysis tool.
  • Deep playground Landing page
    Landing page //
    2019-09-01
  • @RISK Landing page
    Landing page //
    2023-10-17

Deep playground features and specs

  • User-Friendly Interface
    Deep Playground offers a visually intuitive and easy-to-use interface for experimenting with neural networks, making it accessible to beginners.
  • Real-Time Visualization
    It provides real-time visualization of how neural networks adjust during training, which helps in understanding the learned representations and model behavior.
  • Interactive Learning
    Users can interactively change parameters like learning rate, activation functions, and neurons, facilitating a hands-on learning experience about neural networks.
  • Educational Tool
    The platform is specifically designed as an educational tool to help users grasp fundamental machine learning concepts without requiring a complex setup.

Possible disadvantages of Deep playground

  • Limited Complexity
    Deep Playground is limited to simple feedforward neural network architectures, which may not be suitable for exploring more complex models like CNNs or RNNs.
  • Restricted Dataset Options
    The platform offers only a few built-in datasets, limiting the scope of experimentation and not allowing for custom data uploads.
  • Performance Constraints
    As a browser-based tool, it's constrained by client-side processing power, which could slow down computations on less powerful machines.
  • Lack of Advanced Features
    The tool lacks advanced features such as hyperparameter tuning, model evaluation metrics, or integration with more extensive ML frameworks.

@RISK features and specs

  • Comprehensive Risk Analysis
    @RISK provides a detailed and comprehensive risk analysis by using Monte Carlo simulation, which allows users to understand the variability and uncertainty in their models.
  • Excel Integration
    @RISK is integrated directly with Microsoft Excel, making it intuitive for users who are familiar with Excel to build their models and perform risk analysis without needing to learn a new interface.
  • Scenario Analysis
    The software allows users to perform scenario and sensitivity analysis, enabling a deeper understanding of which variables have the greatest impact on their models.
  • Reporting and Visualization Tools
    It offers a variety of tools for reporting and data visualization, making it easy to present findings to stakeholders in a clear and impactful way.
  • Custom Distributions
    @RISK provides flexibility with custom distributions, allowing users to fit their data to a wide range of probability distributions.

Possible disadvantages of @RISK

  • Complexity for Beginners
    The software can be complex for beginners or those not familiar with statistical modeling and Monte Carlo simulations, potentially requiring significant time to learn effectively.
  • Cost
    @RISK can be expensive for individual users or small businesses, which might be a barrier compared to other simpler or free alternatives.
  • Excel Dependency
    Being a tool that works within Excel, its performance and capabilities are limited by the functionalities and limitations of Excel itself.
  • Resource Intensive
    Running large simulations can be resource-intensive, requiring significant processing power and potentially leading to performance issues on less powerful hardware.
  • Steep Learning Curve for Advanced Features
    While basic features might be easy to grasp, mastering the advanced features and functionalities of @RISK could require extensive training and experience.

Category Popularity

0-100% (relative to Deep playground and @RISK)
Simulation
100 100%
0% 0
Governance, Risk And Compliance
Spreadsheets
100 100%
0% 0
Security & Privacy
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 27 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.

Deep playground mentions (27)

  • Ask HN: What are some "toy" projects you used to learn NN hands-on?
    I did a research project on this a while back - and when it comes to understanding deep network learning rate, regularization, hidden layer effects, and activations, I don't think anything is better than [this little web... - Source: Hacker News / 9 months ago
  • 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 / about 1 year ago
  • Introduction to TensorFlow for Deep Learning
    For visualisation and some fun: http://playground.tensorflow.org/. - Source: dev.to / over 1 year ago
  • Visualization of Common Algorithms
    Https://seeing-theory.brown.edu/ https://www.3blue1brown.com/ https://playground.tensorflow.org/. - Source: Hacker News / over 1 year 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 / almost 2 years ago
View more

@RISK mentions (0)

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

What are some alternatives?

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

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

SAI360 - GRC Platforms

GoldSim - GoldSim is the premier Monte Carlo simulation software solution for dynamically modeling complex systems in business, engineering and science.

Oracle Risk Management Cloud - Oracle Risk Management helps to document risks and enforce controls as an integral part of your ERP Cloud deployment

Neuroph - Neuroph is lightweight Java neural network framework to develop common neural network architectures.

Aptible - Aptible is a secure, private cloud deployment platform built to automate HIPAA compliance.