IBM is aiming at creating vast neural networks with a chip implementing one million neurons and 256 million programmable synapses. It is the biggest chip the firm has ever designed: 5...
Machine learning has made big advances in the past few years, thanks in no small part to new methods for scaling out compute-intensive workloads across more cores...
Today we are worshipping the gods of the algorithm, according to one prominent magazine. It’s not a bad comparison. Everything from search results to our machine learning efforts are the basis of a series of equations that purport to solve for something that feels almost ineffable, human...
When we search Google’s web index, we are only searching around 10 percent of the half-a-trillion or so pages that are potentially available...
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...
