Click here to discover dozens of free data science and machine learning related books. Also, most of the upcoming Data Science 2.0 book is available for free here. An earlier version, Data Science 1.0 (also free, somewhat outdated) can be found here.

Use in transforming unstructured data into structured especially in social media monitoring, business intelligence, content recommendations, financial trading and targeted advertising. A live mashup that consumes Alina demonstrates the API's ability to use genetic algorithms and artificial neural networks to analyze historical Bitcoin price fluctuations to predict and automate future trading. Amazon Machine Learning: To find patterns in data. Example uses of this API are applications for fraud detection, forecasting demand, targeted marketing, and click prediction BigML: BigML is a service for cloud-hosted machine learning and data analysis. Users can set up a data source, create a dataset, create a model from the dataset, and then make predictions based on the data.

Why'Deep Learning' is called deep? It is because of the structure of ANNs. Earlier 40 years back, neural networks were only 2 layers deep as it was not computationally feasible to build larger networks. Now it is common to have neural networks with 10 layers and even 100 layer ANNs are being tried upon. Using multiple levels of neural networks in Deep Learning, computers now have the capacity to see, learn, and react to complex situations as well or better than humans. Normally data scientists spend lot of time in data preparation – feature extraction or selecting variables which are actually useful to predictive analytics . Deep learning does this job automatically and make life easier.

Today's hot topic: Resume screening using artificial intelligence Problem: 75% - 88% of resumes received are unqualified Solution: Artificial intelligence that auto-screens thousands of resumes in minutes Results: Candidates are screened with near perfect accuracy and presented to the hiring manager in order of interview priority Outcome: This technology will free up time so talent acquisition can focus on what is most important: interviewing and building their best teams www.Ideal.com Ideal builds software that Talent Acquisition loves. Ideal uses artificial intelligence to help make precise and efficient high-volume hiring decisions. Companies use Ideal's Intelligent Screening technology to sift through the resume noise and instantly identify who to interview.

The presidential campaign made clear that chauvinist attitudes toward women remain stubbornly fixed in some parts of society. It turns out we're inadvertently teaching artificial-intelligence systems to be sexist, too. New research shows that subtle gender bias is entrenched in the data sets used to teach language skills to AI programs. As these systems become more capable and widespread, their sexist point of view could have negative consequences--in job searches, for instance. The problem results from the way machines are being taught to read and talk.

Fei-Fei Li is a big deal in the world of AI. As the director of the Artificial Intelligence and Vision labs at Stanford University, she oversaw the creation of ImageNet, a vast database of images designed to accelerate the development of AI that can "see." And, well, it worked, helping to drive the creation of deep learning systems that can recognize objects, animals, people, and even entire scenes in photos--technology that has become commonplace on the world's biggest photo-sharing sites. Now, Fei-Fei will help run a brand new AI group inside Google, a move that reflects just how aggressively the world's biggest tech companies are remaking themselves around this breed of artificial intelligence. Intel Looks to a New Chip to Power the Coming Age of AI Giant Corporations Are Hoarding the World's AI Talent OpenAI Joins Microsoft on the Cloud's Next Big Front: Chips Facebook Manages to Squeeze an AI Into Its Mobile App Giant Corporations Are Hoarding the World's AI Talent Giant Corporations Are Hoarding the World's AI Talent Alongside a former Stanford researcher--Jia Li, who more recently ran research for the social networking service Snapchat--the China-born Fei-Fei will lead a team inside Google's cloud computing operation, building online services that any coder or company can use to build their own AI. This new Cloud Machine Learning Group is the latest example of AI not only re-shaping the technology that Google uses, but also changing how the company organizes and operates its business.

Recent advances in machine learning have led to innovative applications and services that use computational structures to reason about complex phenomenon. Over the past several years, the security and machine-learning communities have developed novel techniques for constructing adversarial samples--malicious inputs crafted to mislead (and therefore corrupt the integrity of) systems built on computationally learned models. The authors consider the underlying causes of adversarial samples and the future countermeasures that might mitigate them.

Cognitive computing is the simulation of human thought processes in a computerized model. Cognitive computing involves self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works. The goal of cognitive computing is to create automated IT systems that are capable of solving problems without requiring human assistance. Cognitive computing systems use machine learning algorithms. Such systems continually acquire knowledge from the data fed into them by mining data for information.

DeepMind, Google's artificial intelligence outfit, wants to streamline health care by using machine learning to provide medics with intelligent notifications. But not everyone is happy with the piles of data being shared with the company. The project will provide medics across a number of London hospitals with alerts about patients via an app called Streams. The app is meant to provide easy access to patient histories and test results for nurses and doctors. But its AI will also learn to track patterns in patients' blood test data and flag cases that show early signs of kidney injury to the appropriate doctors.

PredictionIO is an open source machine learning server, and is a recent addition to the Apache family.