Resilient back propagation (Rprop), an algorithm that can be used to train a neural network, is similar to the more common (regular) back-propagation. But it has two main advantages over back propagation: First, training with Rprop is often faster than training with back propagation...
Quantitative Investing: Strategies to exploit stock market anomalies for all investors by Fred Piard This book provides straightforward quantitative strategies that any investor can implement with little work using simple, free or low-cost tools and services...
Abstract Support vector machines (SVMs) are promising methods for the prediction of -nancial timeseries because they use a risk function consisting of the empirical error and a regularized term which is derived from the structural risk minimization principle...
WEEKLY DIGEST 2015, February 01 - 08 for Neural Networks in Trading: Do NN need “compound” features, and How do I normalize data for stock prediction? mql5 blogs "Some have tried not using price data at all, and instead using indicators based on that data...
WEEKLY DIGEST 2015, January 24 - 31 for Neural Networks in Trading: Using Neural Networks for Huge Profits mql5 blogs "A neural network is essentially a system of programs and data structures that approximates the operation of the human brain...
WEEKLY DIGEST 2015, January 17 - 24 for Neural Networks in Trading: iknowfirst and artificial intelligence on stock market mql5 blogs “Till today, those kind of algorithms were used only by large institutions, clients like Goldman Sachs...
WEEKLY DIGEST 2015, January 10 - 17 for Neural Networks in Trading: "everyone has an equal chance with the big boys to play in the market" mql5 blogs "We obtained a very significant success in pre-dicting stock price the next day based on a day’s twitter sentiment...
WEEKLY DIGEST 2015, January 03 - 10 for Neural Networks in Trading: "We obtained a very significant success in pre-dicting stock price the next day" mql5 blogs "We obtained a very significant success in pre-dicting stock price the next day based on a day’s twitter sentiment...
WEEKLY DIGEST 2014, December 27 - 2015, January 03 for Neural Networks in Trading & Everywhere: Neural network over-fitting "Overfitting is not only when test error increases with iterations...
WEEKLY DIGEST 2014, December 20 - 27 for Neural Networks in Trading & Everywhere: What Is Neural Programming? Neural programming is used to create software that mimics the brain’s basic functions...
Deep learning - wikipedia Deep learning is part of a broader family of machine learning methods based on learning representations of data. An observation (e.g., an image) can be represented in many ways (e.g...
I’m often asked, especially as the holiday gift-giving season approaches, which books I recommend for investors. I haven’t kept exact count, of course, but over the past quarter-century I have surely read (or tried to read) a couple thousand books on investing...
Optimal construction of day feature in neural networks ============ Prediction Combined with Simple Algorithm Provides Stable Return Any prediction can fail but if it is combined with well-tested buy-sell rules, the result is much better...
Hello Everybody and Thanks for this preliminary interest in my project. It is not something can fit the Freelance Market, and i clearly explain why. I want to create a revolutionary software able to work at the traders side and to guard all the traders decisions...
Abstract This paper reports empirical evidence that a neural networks model is applicable to the statistically reliable prediction of foreign exchange rates...
Stock price predictions have been a field of study from several points of view including, among others, artificial intelligence and expert systems. For short term predictions, the technical indicator relative strength indicator (RSI) has been published in many papers and used worldwide...
Inspired by the article about Neural Networks and made an EA based of that. The article on mql5.com ============ Webinar "Trading with Artificial Neural Networks". The video ============ Japanese scientists have managed to “bypass” inoperative neural pathways. Article...
I'm working on a very complicated EA now it has Artificial Intelligence using a Neural Network with OpenCL and it's self-learning...
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