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Neural Networks Libraries

This is standard library built for flexible neural Networks with performance in mind.
Calling this Library is so simple and takes few lines of code:
   matrix Matrix = matrix_utils.ReadCsv("Nasdaq analysis.csv"); 
   
   matrix x_train, x_test;
   vector y_train, y_test;
    
   matrix_utils.TrainTestSplitMatrices(Matrix,x_train,y_train,x_test,y_test,0.7,42);

   reg_nets = new CRegressorNets(x_train,y_train,AF_RELU_,HL, NORM_MIN_MAX_SCALER); //INitializing network
   
   reg_nets.RegressorNetsBackProp(100, 0.01, LOSS_MSE_, OPTIMIZER_NONE); //Training


//--- Testing the NN

   vector test_pred = reg_nets.RegressorNetsFF(x_test);
   
   Print("Test Acc ",metrics.r_squared(y_test, test_pred));
   

Outputs:

CS      0       19:20:31.261    Regressor Nets Test (EURUSD,H1) [ Epoch 1/100 ] Cost 0.07168254 Acc 0.11997991 | Elapsed 0.017 Seconds  
CS      0       19:20:31.280    Regressor Nets Test (EURUSD,H1) [ Epoch 2/100 ] Cost 0.02692840 Acc 0.66940996 | Elapsed 0.019 Seconds  
CS      0       19:20:31.300    Regressor Nets Test (EURUSD,H1) [ Epoch 3/100 ] Cost 0.00741691 Acc 0.90894538 | Elapsed 0.020 Seconds  
CS      0       19:20:31.330    Regressor Nets Test (EURUSD,H1) [ Epoch 4/100 ] Cost 0.00375571 Acc 0.95389260 | Elapsed 0.029 Seconds  
....
CS      0       19:20:32.410    Regressor Nets Test (EURUSD,H1) [ Epoch 100/100 ] Cost 0.00035787 Acc 0.99560655 | Elapsed 0.010 Seconds  
CS      0       19:20:32.411    Regressor Nets Test (EURUSD,H1) Test Acc 0.994581797713619

Build complex Neural Network systems with Few Lines of MQL5 code:

What are you getting for your money: NEURAL NETS PACKAGE Including DEVELOPMENT SUPPORT.

  • Pattern recognition neural Networks | NN for identifying patterns in the market
  • Regression Neural Networks | Neural networks files for solving regression problems
  • Kohonen Maps | Self organizing maps

Additional files:

  • Data processing libraries
  • Metrics and accuracy measuring libraries
  • Cross validation libraries

Still skeptic?? I have an open repository for Machine Learning on my GitHub, you might wanna give it a shot https://github.com/MegaJoctan/MALE5. It also have Neural Networks capabilities but not to this level, here everything is for VIP members.

The library is always under development so the prices are due to raise with every release, Currently release is V2.5.4. Each release means the new higher price so you better get it now for this cheap price or never.

After a purchase send me a private message to get all the files, there is no way to add all of them in one product.

For an instant response reach me out on Skype | My skype id is: live:.cid.47cd4a057596030f


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This library implements a few functions to simplify the programming of Expert Advisors. * Build your own EA for MT5 / Binance, with a easy support for multisymbol / multytimeframe * Different SFE EAs based on the library provided. * Base signals of SFE EAs are inlcuded in base version. All the Pro filters and management are included in the base version all the 2022. * Customize the provided SFE Lib EA by changing or implementing its rules.. * Review the existing or ask for video tutorials to
The Matrix
Omega J Msigwa
Matrix is the foundation of complex trading algorithms as it helps you perform complex calculations effortlessly and without the need for too much computation power, It's no doubt that matrix has made possible many of the calculations in modern computers as we all know that bits of information are stored in array forms in our computer memory RAM, Using some of the functions in this library I was able to create machine learning robots that could take on a large number of inputs To use this libra
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Esteban Thevenon
EA Toolkit is a library that allows any developer to quickly and easily program Advisor experts. It includes many functions and enumerations such as trailing stop, lot, stop loss management, market trading authorisations, price table updates, trading conditions and many more. Installation + Documentation : You will find all the information to install this library and the documentation of its functions on this GitHub : https://github.com/Venon282/Expert-Advisor-Toolkit WARNING : The installatio
This is standard library built for flexible neural Networks with performance in mind. Calling this Library is so simple and takes few lines of code:    matrix Matrix = matrix_utils.ReadCsv( "Nasdaq analysis.csv" );       matrix x_train, x_test;    vector y_train, y_test;         matrix_utils.TrainTestSplitMatrices(Matrix,x_train,y_train,x_test,y_test, 0.7 , 42 );    reg_nets = new CRegressorNets(x_train,y_train,AF_RELU_,HL, NORM_MIN_MAX_SCALER); //INitializing network       reg_nets.RegressorN
This library is used for sorting key and value arrays, we often need to sort values. like in the python language sorted(key_value.items(), key = lambda kv:(kv[ 1 ], kv[ 0 ])) import function Example of usage scenarios 1. Grid EA orders are sorted according to the opening price void SortedByOpenPride()   {    long     OrderTicketBuffer[];    double   OpenPriceBuffer[];    for ( int i = PositionsTotal ()- 1 ; i>= 0 ; i--)      {        if (m_position.SelectByIndex(i))         {          O
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Linear regression AI powered Indicator: Linear regression is a simple yet effective AI technique that is the foundation of complex neural networks, This indicator is built based on linear regression analysis and tries to make predictions on the upcoming event in the market Inputs : train_bars: This controls the number of bars that the price information will be collected and used to train the AI inside it, The greater this value the better also the slower the indicator becomes during initializati
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Optimus PrimeX: Elevating Your NASDAQ Trading Experience! Unleash the power of Optimus PrimeX, a sophisticated NASDAQ trading robot meticulously crafted to navigate the dynamic landscape of the financial markets. Built upon a trend-following strategy and infused with Artificial Intelligence Biasing, this expert advisor is designed to harness the long-term bullish nature of the NASDAQ index. Strategic Analysis Across Timeframes Optimus PrimeX conducts a comprehensive analysis across the 4-hour, 1
The Matrix
Omega J Msigwa
Matrix is the foundation of complex trading algorithms as it helps you perform complex calculations effortlessly and without the need for too much computation power, It's no doubt that matrix has made possible many of the calculations in modern computers as we all know that bits of information are stored in array forms in our computer memory RAM, Using some of the functions in this library I was able to create machine learning robots that could take on a large number of inputs To use this libra
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Version 3.0 2023.03.07
Pattern recognition neural networks plus softmax layer