13 frameworks for mastering machine learning

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Deep-learning framework Caffe is "made with expression, speed, and modularity in mind." Originally developed in 2013 for machine vision projects, Caffe has since expanded to include other applications, such as speech and multimedia. The distribution includes a set of free and open source reference models for common classification jobs, with other models created and donated by the Caffe user community. Its goals are to make it easier to perform distributed training and deploy to mobile devices, to provide support for new kinds of hardware like FPGAs, and to make use of cutting-edge features like 16-bit floating-point training.


Probabilistic programming from scratch

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Let's take a specific data analysis problem: a simple A/B test for a website. But we're going use a specific, simple inference algorithm called Approximate Bayesian Computation (ABC), which is barely a couple of lines of Python: This function turns the prior distribution into the posterior. I talk about these distributions in more detail in the Orioles, but for this article, the rough idea is sufficient: samples from the prior distribution are our best guesses of the values of the unknown parameter of our system. Let's now write a function that simulates the conversion of n_visitors visitors to a website with known probability p: Here's what happens when we run this function a few times to simulate 100 visitors converting with probability 0.1: Effectively, this function runs a fake A/B test in which we already know the conversion fraction.


5 Negative Pop Culture References About Robots And Artificial Intelligence That Still Haunt Us

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A late '90s classic the film showcased a dystopian world, where the artificially intelligent machines who gained their power source from the sun, fought with humans for supremacy. The Netflix original series Black Mirror -- only three seasons old as of now -- is enough to give any social media, heck, even technology user a nightmare. We won't go into the spoilers here, but episodes like extreme dependency on social media to gain respectability, to creating entire physical humans with the help of their online persona, the dark series showcases a future which is almost believable. While many of the concepts from the series do not seem that far away into the future, even Black Mirror has time and again showcased that there's no such thing as a "one size fits for all" AI.


AI is taking over the cloud and at Box it's starting with images

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Ongoing research, including work from Google's researchers, is improving the ability of algorithms to describe what's happening in images. AI is already the weapon of choice in the battle to dominate cloud computing, with companies that offer on-demand computing--Google, Amazon, and Microsoft among them--all increasingly touting added machine-learning features. He says his company's researchers are exploring ways of applying machine learning to the behavior of its customers. Google's Cloud Vision API can recognize many thousands of everyday objects in images.


Nielsen acquired vBrand, a startup that has developed a machine learning-enabled platform to measure brand exposure and impact in sports programming.

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The acquisition of vBrand's advanced technology supercharges Nielsen Sports' already industry-leading sponsorship measurement capabilities and methodologies, considered among the most robust in sports. "This is an exciting acquisition that demonstrates our continued ambition and commitment to our sports clients.Bringing vBrand's technology into Nielsen Sports' existing sponsorship valuation process will further expand the scale of programming and events it covers around the world. Nielsen Sports' brand exposure data and metrics are considered currency in the global sports marketplace, and we're delighted to strengthen that further with this acquisition," said Howard Appelbaum, President, Nielsen Entertainment. The Nielsen acquisition is the latest milestone in an already well-established relationship between the two companies, as the Tel Aviv-based vBrand is a graduate of Nielsen Innovate--Nielsen's early-stage technology incubator licensed by the Israel Innovation Authority (previously known as the Office of the Chief Scientist of Israel).


Global Artificial Intelligence in Healthcare Market to grow by Over 50%, 2017-2023 - Insights, Opportunity Analysis, Market Shares and Forecasts - Research and Markets

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DUBLIN--(BUSINESS WIRE)--The "Global Artificial Intelligence in Healthcare Market Insights, Opportunity Analysis, Market Shares and Forecast, 2017 - 2023" report has been added to Research and Markets' offering. The rising demand for real time monitoring system and increasing usage of big data in healthcare industry are responsible for the growth of the global Artificial Intelligence in healthcare market. However, ambiguous regulatory guidelines for medical software and reluctance among medical practitioners to adopt Artificial Intelligence based technologies are the factors that restrain the growth of the global Artificial Intelligence in healthcare market. Also, high usage of personal care products among consumers is driving growth of the Artificial Intelligence in healthcare market in North America.


Unsupervised Machine Learning Hidden Markov Models in Python

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While the current fad in deep learning is to use recurrent neural networks to model sequences, I want to first introduce you guys to a machine learning algorithm that has been around for several decades now - the Hidden Markov Model. In this course, you'll learn to measure the probability distribution of a sequence of random variables. We've already covered gradient descent and you know how central it is for solving deep learning problems. This course is also going to go through the many practical applications of Markov models and hidden Markov models.


New Product Forecasting Using Machine Learning - Udemy

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Anamind helps organizations build business planning and forecasting capability. We have incorporated our years of learning from global work experience. Course Design Leads Dr. Steve Miller, Vice President, has over 40 years of vast expertise in business planning and supply chain function working in Fortune 500 companies like Goodyear as well as the teaching experience in Akron University and Herzing University. Rishi Trivedi, CEO, is a Business Planning professional with over 15years of work experience in Fortune 500 companies like Apple, Hewlett Packard and Intel.


Career Alert, August 18

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But when it comes to good judgment, AI is not smarter than the human brain that designed it. Many automated systems perform poorly, to the point that you are wondering if AI is an abbreviation for Artificial Innumeracy. But when it comes to good judgment, AI is not smarter than the human brain that designed it. Many automated systems perform poorly, to the point that you are wondering if AI is an abbreviation for Artificial Innumeracy.


Learning Path: Julia: Explore Data Science with Julia

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You will then be introduced to the basic machine learning techniques, data science models, and concepts of parallel computing. In 2000, he switched over to partly teach and partly develop software (KHM Mechelen, CVO Antwerp). Jalem Raj Rohit is an IIT Jodhpur graduate with a keen interest in machine learning, data science, data analysis, computational statistics, and natural language processing (NLP). Rohit currently works as a senior data scientist at Zomato, also having worked as the first data scientist at Kayako.He is part of the Julia project, where he develops data science models and contributes to the codebase.