BigData News Monday, March 26 Cheat sheet dump, Data science cheat, Machine learning & more…


BigData News TLDR / Table of Contents

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30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets

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  • This collection of data science cheat sheets is not a cheat sheet dump, but a curated list of reference materials spanning a number of disciplines and tools.
  • Nothing takes the place of meaningful and substantive study, but these cheat sheets (that’s really not a great term for them) are a handy reference in a pinch or for reinforcing particular ideas.
  • All images link back to the cheat sheets in their original locations.

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[/vc_column_text][vc_column_text el_class=”topfeed-embedly”]30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets[/vc_column_text][/vc_column][/vc_row][vc_row el_id=”Gigaom-How-Machines-Learn-The-Top-Four-Approaches-to-ML-in-Business”][vc_column width=”1/2″][vc_separator][vc_column_text]

Gigaom | How Machines Learn: The Top Four Approaches to ML in Business

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  • This functional mapping takes the general form y = f(x) specify your target output y, provide your inputs x, and the ML algorithm will learn the optimal f() by finding patterns in the data.
  • Popular supervised learning regression – Random forest – Multi-layer perceptron – Convolutional deep neural regression – Support vector machines – Convolutional deep neural networks – Naive Bayes – – – – – Unsupervised Learning – – Unsupervised learning is used when training data has no specific label for the algorithm…
  • Popular unsupervised learning algorithms: – – – – – K-means clustering – Principal component analysis – Non-negative matrix factorization – Hidden Markov model – Hebbian Learning – – At Vidora, weve seen that collecting labeled data at scale is a challenge for many business organizations, but unlabeled data is relatively…
  • Popular reinforcement learning difference – Monte Carlo tree search – Sarsa – – – – – ML and Your Business – – Each of supervised, unsupervised, semi-supervised, and reinforcement learning has shown meaningful success in the business world.
  • As the practical scope of machine learning broadens, fluency in its key concepts becomes an increasingly important business skill even for those with no data science experience.

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