Cryptomon

Cryptomon

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Last Update

Apr 3, 2018

Modern intelligent trading indicators and tools for traders with the power of machine learning.
Pre-ICO 15%
Apr 3, 2018
May 3, 2018
100% completed
Raised funds - no Data
past
  • 1 CMN
    =
    0.5525 USD
Token Details
Ticker
CMN
Company Details
Registered Country
Slovakia
Additional Details
Platform
Ethereum
Categories
Platform

About Cryptomon

Cryptomon is ready to use platform with real prediction algorithms and custom indicators based on machine learning. First version of Cryptomon was released in June 2017, and since then we built community of experts in machine intelligence around the Cryptomon platform. All these give us a significant competitive advantage over other trading tools and platforms which are still in development and they have using of ML only as a future milestone.

Cryptomon provides a set of predictions and modern indicators for mastering trading strategies. Any crypto trader armed with computational power and data science can make smarter and faster trading decisions and maximize trading profits. So why to use legacy indicator like MA (Moving Average), when we have machine intelligence?

Community
Sharing experience and knowledge transfer are the basis of evolutionary development on any field, especially while developing new prediction algorithms. Members help each other to move to the next level of development. That's why in Cryptomon a lot of attention is paid to the community. All Cryptomon prediction algorithms and machine learning indicators are open sourced on our GitHub page, so everyone can enhance existing or develop new prediction algorithms with our ML stack from https://cryptomon.io/lab. Every enhancement, documented with better prediction performance will be rewarded with CMN tokens (considering use https://gitcoin.co or https://gittoken.org). Detailed contribution reward policy will be released in Q2 2018. 

 

Features

- Trade signals notifications

- Prediction algorithms and indicators

- Machine learning

- TensorFlow

Technical Info

K-nearest neighbors
The k-nearest neighbors (KNN) algorithm is a non-parametric algorithm that can be used for either classification or regression. Non-parametric means that it makes no assumption about the underlying data or its distribution. It is one of the simplest Machine Learning algorithms, and has applications in a variety of fields, ranging from the healthcare industry, to the finance industry. More info on wikipedia. Source code available on GitHub.

Multilayer perceptron 
A multilayer perceptron (MLP) is a feedforward artificial neural network model that maps sets of input data onto a set of appropriate outputs. An MLP consists of multiple layers of nodes in a directed graph, with each layer fully connected to the next one. Except for the input nodes, each node is a neuron (or processing element) with a nonlinear activation function. MLP utilizes a supervised learning technique called backpropagation for training the network.MLP is a modification of the standard linear perceptron and can distinguish data that are not linearly separable. More info on wikipedia. Source code available on GitHub.

LSTM 
A powerful type of neural network designed to handle sequence dependence is called recurrent neural networks. The Long Short-Term Memory network or LSTM network is a type of recurrent neural network used in deep learning because very large architectures can be successfully trained. More info on wikipedia.

WTBS indicator
When To Buy and Sell technical indicator is based on CNN - Convolutional Neural Network. NN use a variation of multilayer perceptrons designed to require minimal preprocessing. They are also known as shift invariant or space invariant artificial neural networks (SIANN), based on their shared-weights architecture and translation invariance characteristics. Convolutional networks were inspired by biological processes in which the connectivity pattern between neurons is inspired by the organization of the animal visual cortex. More info on wikipedia. Source code available on GitHub.

Cryptomon Roadmap

  • June 2017

  • First version with basic predictions
    BTC subscriptions
  • Q3 - Q4 2017

  • Cryptomon Lab with ML stack
    New indicators in Lab - WTBS (When To Buy and Sell) indicator, WM (Whale Moves) indicator
    Multilayer perceptron and K-nearest neighbors v2 implemented on web
    WTBS v1 indicator implemented on web
  • Q1 2018

  • CMN token public presale and sale
    CMN token based subscriptions, BTC subscriptions disabled
    WM v1 indicator implementation on web
    Bounty program start
  • Q2 2018

  • CMN reward program start
    Requests for enhancements listed on https://gitcoin.co or https://gittoken.org
    New prediction algorithms and indicators
    Support for the new exchanges and currency pairs
    CMN token on more than 2 exchanges
    Signals dashboard
  • Read More
  • Q3 2018

  • 0x protocol signals (support for any ERC20 tokens)
    Trade signals notifications for Telegram app
    Support for the new exchanges and currency pairs
    New prediction algorithms/indicators with monitoring of news and social feeds
  • Q4 2018

  • Containerized projects in Lab - user can deploy and execute project directly from web with visible results
    Integrations with 3rd parties like https://tradingview.com - Cryptomon indicators on interactive chart, or integrations with trading bots
    Support for the new exchanges and currency pairs
  • Q1 - Q2 2019

  • Lab marketplace
    CMN token on more than 5 exchanges

Cryptomon Team

Verified 100%

Peter Klobusnik
CEO / FOUNDER / ARCHITECT
verified
Peter Kotula
CTO / FOUNDER / ARCHITECT / LEAD SOFTWARE DEVELOPE...
verified
Martin Hazy
SUPPORT / MARKETING SPECIALIST
verified
Juraj Burian
ARCHITECT / LEAD SOFTWARE DEVELOPER
verified

Cryptomon Interviews

Peter Klobusnik
As a team member, сan you tell us about your role in the ICO project? What do you think about idea?
Working for more than 12 years in the IT industry as an R&D expert and entrepreneur. Currently focusing on deep learning and its applications on time series analytics. Experience in trading and trading algorithms development since 2013.
Peter Kotula
As a team member, сan you tell us about your role in the ICO project? What do you think about idea?
Working in the IT industry since 2006, in various positions, as developer, project manager, architect and DevOps. Blockchain and smart contracts enthusiast. Currently working on Fast/Big Data projects.
Martin Hazy
As a team member, сan you tell us about your role in the ICO project? What do you think about idea?
Martin is working almost 10 years in IT industry for global companies. Except his passion for music and art he is focusing on searching trade patterns and trading strategies in cryptocurrencies and other markets either.
Juraj Burian
As a team member, сan you tell us about your role in the ICO project? What do you think about idea?
Born in 1970, in 1994 finished university study with specialization on theoretical physics, then start developing software on professional basis. In present time working on Big Data projects, distributed calculations with focus on functional programming techniques.
Favorite languages are Scala and Haskell, favorite toolset SMACK.

Cryptomon Last News

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