The 7 Steps of Machine Learning

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How can we tell if a drink is beer or wine? Machine learning, of course! In this episode of Cloud AI Adventures, Yufeng walks through the 7 steps involved in applied machine learning. The 7 Steps of Machine Learning article: https://goo.gl/XEo6i2 Watch more episodes of AI Adventures here: https://goo.gl/UC5usG TensorFlow […]

What Is Big Data? & How Big Data Is Changing The World!

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In this video, we’ll be discussing big data – more specifically, what big data is, the exponential rate of growth of data, how we can utilize the vast quantities of data being generated as well as the implications of linked data on big data. [0:30-7:50] – Starting off we’ll look […]

Predicting the Winning Team with Machine Learning

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Can we predict the outcome of a football game given a dataset of past games? That’s the question that we’ll answer in this episode by using the scikit-learn machine learning library as our predictive tool. Code for this video: https://github.com/llSourcell/Predicting_Winning_Teams Please Subscribe! And like. And comment. More learning resources: https://arxiv.org/pdf/1511.05837.pdf […]

Support Vector Machine (SVM) – Fun and Easy Machine Learning

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Support Vector Machine (SVM) – Fun and Easy Machine Learning ►FREE YOLO GIFT – http://augmentedstartups.info/yolofreegiftsp ►KERAS COURSE – https://www.udemy.com/machine-learning-fun-and-easy-using-python-and-keras/?couponCode=YOUTUBE_ML ►MACHINE LEARNING COURSES -http://augmentedstartups.info/machine-learning-courses ———————————————————————— A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data (supervised learning), the algorithm […]

The human insights missing from big data | Tricia Wang

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Why do so many companies make bad decisions, even with access to unprecedented amounts of data? With stories from Nokia to Netflix to the oracles of ancient Greece, Tricia Wang demystifies big data and identifies its pitfalls, suggesting that we focus instead on “thick data” — precious, unquantifiable insights from […]