This matrix can be used for 2-class problems where it is very easy to understand, but can easily be applied to problems with 3 or more class values, by adding more rows and columns to the confusion matrix. Let's make this explanation of creating a confusion matrix concrete with an example. Let's pretend we have a two-class classification problem of predicting whether a photograph contains a man or a woman. We have a test dataset of 10 records with expected outcomes and a set of predictions from our classification algorithm. Let's start off and calculate the classification accuracy for this set of predictions. The algorithm made 7 of the 10 predictions correct with an accuracy of 70%. First, we must calculate the number of correct predictions for each class. Now, we can calculate the number of incorrect predictions for each class, organized by the predicted value.

Although open source code in Python and R is popular because of its low cost, flexibility, and power, the time required to properly create code and ensure that it is working correctly can be frustrating. Not everyone is a programmer or wants to program! That's why the announcement by IBM in June about IBM Data Science Experience is such a game-changer! IBM Data Science Experience is a way for data scientists to collaborate and work on data science programs in the most efficient way possible. What if the collaboration could be extended to the data scientist or analyst who wants to build predictive models without code?

Few areas of technology are attracting as much interest as self-driving cars. Wall Street Journal Business Editor Jason Anders discussed the heart of that technology with Jen-Hsun Huang, chief executive of Nvidia Corp., whose chips are used to power autonomous driving and other artificial-intelligence applications. ANDERS: What can self-driving cars do today that they couldn't do a year ago? HUANG: Well, the biggest problem is that the car has to be able to perceive the environment. Reasoning, planning and learning are a big part of artificial intelligence.

We have all had the experience. You are doing some on-line shopping. You drop a few items into your shopping cart and the website gets'helpful.' Across the bottom of the screen you see a collection of other items and you are told that they might be of interest to you. And the odd thing is, they mostly are kind of interesting.

The House of Lords has passed the Investigatory Powers Bill, putting the huge spying powers on their way to becoming law within weeks. The bill – which forces internet companies to keep records on their users for up to a year, and allows the Government to force companies to hack into or break things they've sold so they can be spied on – has been fought against by privacy campaigners and technology companies including Apple and Twitter. But the Government has worked to continue to pass the bill, despite objections from those companies that the legislation is not possible to enforce and would make customers unsafe. In its facilities, JAXA develop satellites and analyse their observation data, train astronauts for utilization in the Japanese Experiment Module'Kibo' of the International Space Station (ISS) and develop launch vehicles 23/40 The robot developed by Seed Solutions sings and dances to the music during the Japan Robot Week 2016 at Tokyo Big Sight. At this biennial event, the participating companies exhibit their latest service robotic technologies and components 24/40 The robot developed by Seed Solutions sings and dances to music during the Japan Robot Week 2016 at Tokyo Big Sight 25/40 Government and industry are working together on a robot-like autopilot system that could eliminate the need for a second human pilot in the cockpit 26/40 Aurora Flight Sciences' technicians work on an Aircrew Labor In-Cockpit Automantion System (ALIAS) device in the firm's Centaur aircraft at Manassas Airport in Manassas, Va.

Intel is taking a new direction in chip development as it looks to the future of artificial intelligence, with the company betting the technology will pervade applications and web services. The company on Thursday said it is developing new chips that will handle AI workloads, which will increasingly be a part of its chip future. For now, the AI chips will be released as specialized primary chips or co-processors in computers and separate from the major product lines. But over time, Intel could adapt and integrate the AI features into its mainstream server, IoT, and perhaps even PC chips. The AI features could be useful in servers, drones, robots, and autonomous cars.

An Introduction to Statistical Learning: with Applications in R Overview of statistical learning based on large datasets of information. The exploratory techniques of the data are discussed using the R programming language. Modeling With Data This book focus some processes to solve analytical problems applied to data. In particular explains you the theory to create tools for exploring big datasets of information. Big Data, Data Mining, and Machine Learning: Value Creation for Bus... On this resource the reality of big data is explored, and its benefits, from the marketing point of view.

The world is evolving at thunder-speed, and an increasing number of machines are being designed to catch up with humans in many activities. Ever since IBM's Artificial Intelligence (AI) Deep Blue defeated the world Chess Champion in 1997 a lot has been going on. Self-driving cars, close-to-perfect face-recognition software, stock investment geniuses, chatbots and even AI doctors are close to be (or already are) part of our daily lives. One has just to see how Watson, also an IBM AI robot "destroyed" the other (human) players in a game of Jeopardy in 2011. A few years ago, AI boundaries were given by the codes written in the robot's programming.

Machine learning is on a steep adoption curve and making its inroads in our daily lives and work. The application of the technology won't be an issue at all. There's an abundance of meaningful value propositions for many functional areas, business processes and roles across multiple industries. Software vendors of enterprise business solutions are focusing their product development on machine learning and other related artificial intelligence technologies. CEO Bill McDermott of SAP said that intelligent applications will fundamentally change the way you do work in the enterprise in the next decade.

The artificial intelligence (AI) non-profit OpenAI has agreed to partner with Microsoft to develop "cloud brains" to test its experiments. The organization, which is backed by Elon Musk, has signed an agreement that will allow it to run large-scale experiments using the company's Azure cloud services. OpenAI aims to discover more about deep learning and AI, while Microsoft will use the partnership to create new tools and technologies that use AI. OpenAI was one of the first adopters of Microsoft's Azure N-Series Virtual Machines service that was designed to handle the intense computing workloads that are needed to run simulations and deep learning projects. The service is powered by Nvidia's graphics chips and will be made generally available starting in December.