MonumentAI
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About
MonumentAI is a no-code predictive intelligence platform that empowers users to build and deploy predictive models without needing coding skills. It boasts high productivity, enabling users to compare multiple models, analyze results, and deploy solutions within minutes. MonumentAI produces clear, easily understandable reports suitable for diverse audiences. It scales from local use on a laptop to cloud deployments for increased computational power, supporting datasets up to 1 terabyte. The platform offers a variety of applications including churn prediction, demand forecasting, personalized recommendations, and more. It integrates with various cloud providers and aims to improve productivity and reduce costs by 80-90%. A free live demo is available.
Platform
Features
• predictive intelligence
• scalable
• no-code
• algorithm recommendation
• multiple model comparison
• runs locally and in the cloud
• clear reports
• high-productivity
FAQs
What do I have to learn to use Monument?
There is a learning curve with Monument, but it is much less than any other AI or machine learning curve that requires coding. A great place to start learning is on our Youtube channel, which shows easy-to-use examples to get started.
How secure is Monument?
Monument is completely self-contained. You don't need an internet connection to use Monument. You can check this by turning off your internet and running algorithms. It all runs locally. You can't find this anywhere else. There is no risk of people snooping in on your work.
What is the max data size Monument can support?
Monument supports data sets up to 1 terabyte.
How can Monument used for cryptocurrency?
Monument was created for algorithmic forecasting and makes algorithmic trading accessible for everyday cryptocurrency traders.
How does Monument help me trade?
When you select a pair to analyze, Monument will let you know where various algorithms anticipate the price to be in the future. To do this, drag and drop an algorithm over the data.
How is Monument different from crypto bots?
Monument allows you to build your own bots that no one else has access to. You get to choose the algorithms, parameters, and time intervals.
Is there backtesting?
There is currently no back testing, but we are planning on adding it in the future.
What is backtesting?
You would build a model that, as an example, says my target price is $9000 and every time it is below $8500 buy bitcoin and every time it is above $9500 sell bitcoin. Then you would simulate what would have been your profits if you did that strategy for the past month. To give a sense of what you might expect if you started doing that into the future.
What is the trading time frame Monument works with?
Monument works with any time interval. It all depends on the data that is being uploaded.
Where does the pair data come from?
We have direct integration with Binance.
How do I know which algorithm to use?
It takes some practice to understand which algorithms are appropriate for which datasets. For example, certain algorithms do better when there is higher volatility in the training data. Whereas other algorithms do better when they are large, slow macro price movements.
What are algorithm parameters used for?
Sometimes it's necessary to adjust the algorithm parameters in the interface to improve the results. Generally, a good workflow is to try several algorithms on the same data and see if they are agreeing generally, or if there is really wide disagreement.
What makes an algorithm more likely to be accurate than another?
You want to pay attention to the "validation error rate", which is reported in the bottom left info box in the model interface. You want that number to be as negative as possible. The more negative that number is, the more likely the model is to be accurate. You want to experiment with algorithms and parameters until you find the lowest validation error rate.
What is a good gauge for the "validation error rate"? How far negative should the number be?
The more negative the number the better the model is. Models can always get better. The judgement on whether the validation error rate is good or bad comes with experience. That being said, it doesn't _have_ to be negative per se, it could just be the lowest positive number you can get to. 10 is better than 100, -1 is better than 10, etc..
What is the chart next to the "validation error rate"?
That chart shows you how the error rate improves with each training round. The x axis is each round. If the line is flat that means that it's not improving much each time. If there is a slope downwards, it means you might get better performance if you increase the number of training rounds.
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