The latest version of Deep Learning Application (Bayou) will help humans in programming. With the help of just a little information and some keywords, Bayou can almost predict the programmers brain. The researchers have used method of Neural Sketch Learning to train its Neural Network.  It can easily take over forums like Stack-Overflow because of its instant reply to programming problems. Read more at: 

https://www.futurity.org/artificial-intelligence-bayou-coding-1740702/

E-Book business communities generate a lot of revenue everyday but sometimes it is difficult for author(s) to earn decent amount because of lack of preparation and research. No matter how unique and interesting your content is, if it doesn't appear on the first or second page of search results, it's highly unlikely that a visitor would ever read it. The story doesn't end here, one must cleverly select the title and cover which attract the reader as it changes the way we think. A neural network approach for the determination of most titles using Doc2Vec can be adopted to increase revenue. It involves training a thin two-layer neural network, which operates in unsupervised mode and form clusters of most similar words (using cosine similarity metric) based on context.

To read more about the technical implications here: http://www.datasciencecentral.com/profiles/blogs/use-neural-networks-to-find-the-best-words-to-title-your-ebook

Fraud is one of the major issues in today’s business world. It was found that 8% increase over last year in the cost per dollar of fraud losses and online retailers are the worst hit as fraudulent transactions grew 32.1% in 2015. Nowadays, data analysis has come to rescue organizations from fraud as it allows companies to create fraud risk profiles and then use existing data to identify potential fraudulent activity. This article explores the commonly used data analysis techniques used to search out fraudulent transactions. They are: Pattern Recognition, Outlier Detection, Regression Analysis, Semantic Modeling, Neural Network, and Anomaly Detection. Read more at: http://it.toolbox.com/blogs/itmanagement/how-to-detect-fraud-using-data-analysis-74726