Jan 07, 21: #AnalyticsClub #Newsletter (Events, Tips, News & more..)

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[  COVER OF THE WEEK ]

image
Statistics  Source

[ FEATURED COURSE]

Deep Learning Prerequisites: The Numpy Stack in Python

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The Numpy, Scipy, Pandas, and Matplotlib stack: prep for deep learning, machine learning, and artificial intelligence… more

[ FEATURED READ]

Big Data: A Revolution That Will Transform How We Live, Work, and Think

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“Illuminating and very timely . . . a fascinating — and sometimes alarming — survey of big data’s growing effect on just about everything: business, government, science and medicine, privacy, and even on the way we think… more

[ TIPS & TRICKS OF THE WEEK]

Data Have Meaning
We live in a Big Data world in which everything is quantified. While the emphasis of Big Data has been focused on distinguishing the three characteristics of data (the infamous three Vs), we need to be cognizant of the fact that data have meaning. That is, the numbers in your data represent something of interest, an outcome that is important to your business. The meaning of those numbers is about the veracity of your data.

[ DATA SCIENCE Q&A]

Q:What is the difference between supervised learning and unsupervised learning? Give concrete examples
?

A: * Supervised learning: inferring a function from labeled training data
* Supervised learning: predictor measurements associated with a response measurement; we wish to fit a model that relates both for better understanding the relation between them (inference) or with the aim to accurately predicting the response for future observations (prediction)
* Supervised learning: support vector machines, neural networks, linear regression, logistic regression, extreme gradient boosting
* Supervised learning examples: predict the price of a house based on the are, size.; churn prediction; predict the relevance of search engine results.
* Unsupervised learning: inferring a function to describe hidden structure of unlabeled data
* Unsupervised learning: we lack a response variable that can supervise our analysis
* Unsupervised learning: clustering, principal component analysis, singular value decomposition; identify group of customers
* Unsupervised learning examples: find customer segments; image segmentation; classify US senators by their voting.

Source

[ VIDEO OF THE WEEK]

#BigData @AnalyticsWeek #FutureOfData #Podcast with Joe DeCosmo, @Enova

 #BigData @AnalyticsWeek #FutureOfData #Podcast with Joe DeCosmo, @Enova

Subscribe to  Youtube

[ QUOTE OF THE WEEK]

For every two degrees the temperature goes up, check-ins at ice cream shops go up by 2%. – Andrew Hogue, Foursquare

[ PODCAST OF THE WEEK]

Understanding Data Analytics in Information Security with @JayJarome, @BitSight

 Understanding Data Analytics in Information Security with @JayJarome, @BitSight

Subscribe 

iTunes  GooglePlay

[ FACT OF THE WEEK]

40% projected growth in global data generated per year vs. 5% growth in global IT spending.

Sourced from: Analytics.CLUB #WEB Newsletter

7 thoughts on “Jan 07, 21: #AnalyticsClub #Newsletter (Events, Tips, News & more..)”

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