Logistic Regression for Machine Learning - Machine Learning Mastery

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Logistic regression is another technique borrowed by machine learning from the field of statistics. It is the go-to method for binary classification problems (problems with two class values). In this post you will discover the logistic regression algorithm for machine learning. This post was written for developers interested in applied machine learning, specifically predictive modeling. You do not need to have a background in linear algebra or statistics.


IEEE Xplore Abstract - Runtime Behavior Adaptation for Real-Time Interactive Games

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Intelligent agents working in real-time domains need to adapt to changing circumstance so that they can improve their performance and avoid their mistakes. AI agents designed for interactive games, however, typically lack this ability. Game agents are traditionally implemented using static, hand-authored behaviors or scripts that are brittle to changing world dynamics and cause a break in player experience when they repeatedly fail. Furthermore, their static nature causes a lot of effort for the game designers as they have to think of all imaginable circumstances that can be encountered by the agent. The problem is exacerbated as state-of-the-art computer games have huge decision spaces, interactive users, and real-time performance that make the problem of creating AI approaches for these domains harder.


This Week's Awesome Stories From Around the Web (Through April 2) - Singularity HUB

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ARTIFICIAL INTELLIGENCE: How Google Plans to Solve Artificial Intelligence Tom Simonite MIT Technology Review "It's supposed to be just an early checkpoint in an effort Hassabis describes as the Apollo program of artificial intelligence, aimed at "solving intelligence, and then using that to solve everything else"...Hassabis wants to create what he calls general artificial intelligence--something that, like a human, can learn to take on just about any task." ROBOTICS: What Is a Robot? Adrienne LaFrance The Atlantic "What is a robot, anyway? This has become an increasingly difficult question to answer. Yet it's a crucial one...Whether we will end up losing a piece of our humanity because they are here is unknowable today.


Self-driving Car

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The inspiration originates from the course Artificial Intelligence for Robotics - Programming a Robotic Car. The car is using an algorithm called Hybrid A star to find the shortest path to the goal, which is the same algorithm used by the self-driving car Junior. You can read more about it here: Explaining the Hybrid A Star pathfinding algorithm for selfdriving cars. The car is using a PID controller to follow that path. The white and gray lines are Reeds-Shepp Paths which Hybrid A* is using to increase the performance of the algorithm.


Largest network of cortical neurons mapped from 100 terabytes data set

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Neuroscientists have constructed a network map of connections between cortical neurons, traced from a 100 terabytes 3D data set. The data were created by an electron microscope in nanoscopic detail, allowing every one of the "wires" to be seen, along with their connections. Some of the neurons are color-coded according to their activity patterns in the living brain. The largest network of the connections between neurons in the cortex to date has been published by an international team of researchers from the Allen Institute for Brain Science, Harvard Medical School, and Neuro-Electronics Research Flanders (NERF). In the process of their study*, the researchers developed new tools that will be useful for "reverse engineering the brain by discovering relationships between circuit wiring and neuronal and network computations," says Wei-Chung Lee, Ph.D., Instructor in Neurobiology at Harvard Medicine School and lead author of a paper published this week in the journal Nature.


The Reactive Machine Learning book is live! -- Data Engineering

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At long last, I'm thrilled to announce that Reactive Machine Learning Systems is now available in early access form. I've been working on this book since the original post on reactive machine learning, last year. It's great to be able to finally share the first phase of this work with the world. The book is much like the data engineering collection here on Medium. I've tried to catalogue all of the real world details of building a full machine learning system that you don't hear about in other algorithm-focused books.


India to get updated version of Cortana this summer - Artificial Intelligence Online

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Cortana is one of MicrosoftMicrosoft Cloud Tool Moves Enterprise Analytics Data Easily. Read more ... »'s key focuses this year, and the personal assistantMicrosoft Launches New Emotion API Tool That Can Recognize Several Emotions In Photos. Read more ... » is set to receive more features with the upcoming Anniversary Update for Windows 10. "We think this can have as profound an impact as the previous platform shifts have had", Nadella said in his keynote speechMicrosoft Launches New Emotion API Tool That Can Recognize Several Emotions In Photos. In gaming-related news, Microsoft has also incorporated Xbox into Windows. For now, the preview bots are already available on Skype for the latest versions on the Windows Desktop, iPhone, iPad, and Android.


Google says robots are going to be bigger than search

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Machine learning is the hot new thing in Silicon Valley. In an interview with the Times, Google cloud executive Urs Hölzle predicted that the business of renting out machine learning capabilities will one day overtake the company's advertising revenue. To put that in perspective, search ads made Google an eye-popping 16.4 billion in profits in 2015. Machine learning is a branch of computer science where algorithms can train themselves in pattern recognition. Crucially, it doesn't require a programmer to orient the algorithm to what works or doesn't work in a given domain -- it can learn on its own.


The Story Behind Siri -- The Startup

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A pioneer in Artificial Intelligence, Adam Cheyer has spent most of his life living by what he calls "Verbally Stated Goals" -- that is, continuously striving to do and achieve more each year. As a child, he dreamed of becoming a magician and, in many ways, he did just that: in 2008, as inventor, computer scientist, engineer, and entrepreneur, he co-created the world's first intelligent personal assistant, Siri, with Dag Kittlaus and Tom Gruber. Siri, Inc. was a technology company borne out of SRI International, a nonprofit research unit, to create a highly clever and personable virtual assistant for smartphone consumers. By 2010, the company had been acquired by Apple Inc., and the Siri app was incorporated into Apple's iPhone 4S handsets. Cheyer became Director of Engineering for the iPhone/iOS team at Apple, where he remained for two years before leaving to spend more time with his family and to pursue personal endeavours. Cheyer is also a founding member of Change.org, a social network for positive social change, and is co-founder of Genetic Finance, which applies advanced artificial intelligence to solve problems within a wide range of industries, including financial trading, insurance, computer networking, and electronics design. Newnham: Take me back to your childhood. What first excited you about technology? Adam Cheyer: As a child, I was allowed to watch an hour of TV a week, and in that time, I got my fill of commercials selling me on the latest toys.


Machine Learning Software Engineer at AimBrain

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At AimBrain, we are revolutionising the way we do authentication. We are developing a state-of-the-art biometric authentication platform to allow easy access to robust biometric authentication in any mobile or IoT device. Join our highly technical founding team as we make biometrics the main authentication method of the future.