ANNs and Predictive Analytics
ANNs and Predictive Analytics ANNs have the potential to provide high fault tolerance. A problem in a single processing element will not stop the network from producing output. They are good at pattern recognition, classification and optimization. Among other things, this means that they can help with tasks such as air traffic control, recognizing handwritten digits and credit card fraud detection. Neural Networks are a Machine Learning Algorithm Machine learning algorithms like neural networks produce results that can be hard to interpret. There are plenty of anecdotes out there of seemingly perfect solutions that turn out to stem from bugs or simple biases in the data set. Neural networks are able to identify patterns in unlabeled, real-world data — such as pictures, text and video recordings — and apply those findings to new problems. This is what makes them powerful tools for image recognition, natural language processing and recognizing patterns in customer browsing histories. Inputs are fed into a network through layers of input units, hidden units and output units, which all have their own weightings and thresholds. Each time an incorrect prediction is made, the model learns by providing a feedback loop that adjusts internal weights. This is known