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April 2018 Blog Posts (88)

Big Data’s Mathematical Mysteries

This article was posted by Ingrid Daubechies on Quanta Magazine. Ingrid is the James B. Duke Professor of Mathematics and Electrical and Computer Engineering at Duke University. She served as president of the International Mathematical Union from 2011 to 2014.

Machine learning works spectacularly well, but mathematicians aren’t quite sure why.…

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Added by Emmanuelle Rieuf on April 18, 2018 at 8:30am — No Comments

Deciphering information and misinformation: Inspired by the book "A Field Guide to Lies and Statistics"

They are in combat side-by-side, staring back at you like identical twins, one of them will help you and the other one will hurt you, who are they?

They are information and misinformation, writes neuroscientist Daniel Levitin in his book “A field guide to lies and statistics”.

But are these two really fighting on a level playing field? New research findings published in Science magazine show that things are much more serious than we might have thought.…

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Added by Tom Bransby on April 18, 2018 at 6:30am — No Comments

How to do Speech Recognition with Deep Learning

This article was posted by Adam Geitgey. Adam is Interested in computers and machine learning and he likes to write about it.

Speech recognition is invading our lives. It’s built into our phones, our game consoles and our smart watches. It’s even automating our homes. For just $50, you can get an Amazon Echo Dot — a magic box that…

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Added by Emmanuelle Rieuf on April 18, 2018 at 3:00am — No Comments

Transfer Learning –Deep Learning for Everyone

Summary: Deep Learning, based on deep neural nets is launching a thousand ventures but leaving tens of thousands behind.  Transfer Learning (TL), a method of reusing previously trained deep neural nets promises to make these applications available to everyone, even those with very little labeled data.

 

Deep Learning, based on…

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Added by William Vorhies on April 17, 2018 at 12:25pm — No Comments

6 Reasons for Investing Some Time to Learn Tableau

I have seen a few mentions of Tableau in my feed and wanted to offer some thoughts on why I strongly suggest data scientists investing a few hours to learn the basics of Tableau.

(1)   Tableau is widely used. Many people that have reporting functions rely on Tableau so knowing the basics is helpful to your business and clients.

(2)   Tableau is great for quick data visualizations and for generating some…

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Added by Howard Friedman on April 17, 2018 at 9:23am — No Comments

How HR Analytics play in Digital Age

Today every company is acting on the digital transformation or at least talking about digital transformation. While it is important to drive it by analyzing customer behavior, it is extremely important to understand who from your organization is acting upon it – your employees.

Hence…

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Added by Sandeep Raut on April 17, 2018 at 1:30am — No Comments

Machine Learning with C++ - Polynomial Regression (CPU)

There are a lot of articles about how to use Python for solving Machine Learning problems, with this article I start series of materials on how to use modern C++ for solving same problems and which libraries can be used. I assume that readers are already familiar with Machine Learning concepts and will concentrate on programming issues only.

The first part is about creating Polynomial Regression model with XTensor library. This is C++ library for numerical analysis with…

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Added by Kyrylo Kolodiazhnyi on April 17, 2018 at 12:30am — 6 Comments

Google Deepmind: The Importance of Artificial Intelligence

Developments in Artificial Intelligence (A.I.) are happening faster today than ever before. However, the nature of progress in A.I. is such that massive technological breakthroughs…

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Added by Ronald van Loon on April 17, 2018 at 12:00am — No Comments

Why Are Data Science Leaders Running for the Exit?

Guest blog post by Edward Chenard, Contributor at DataScience.com.

I've had several conversations recently with people I know in the data science space that always start out about business and then drift to the state of data science as a whole. One theme constantly comes up in these conversations: There are a lot of people currently running data…

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Added by Vincent Granville on April 16, 2018 at 5:30pm — 17 Comments

Elements of Modern Data Science, AI, Big Data and ML

Guest blog post by Michael Li, Head of Analytics and Data Science at LinkedIn.

I’m sure everyone who has been following tech industry news knows about “big data” and “AI.” Although there is no industry-consistent definition for either term, most people tend to agree…

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Added by Vincent Granville on April 16, 2018 at 5:00pm — 4 Comments

Unsupervised Learning an Angle for Unlabelled Data World

This is our second post in this sub series “Machine Learning Types”. Our master series for this sub series is “Machine Learning Explained”.

Unsupervised Learning; is one of three types of machine learning i.e. Supervised Machine Learning, Unsupervised…

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Added by Vinod Sharma on April 16, 2018 at 8:00am — No Comments

Data Dictionary to Meta Data II -- Simple Text Wrangling and Factor Creation in R

My blog last week articulated a first shot at automating the creation of meta data…

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Added by steve miller on April 16, 2018 at 6:30am — No Comments

44 Original Data Science and Machine Learning Articles

Written exclusively for Data Science Central, by Vincent Granville. These articles are intended for non-experts, written in simple English, and particularly suited for professionals managing a data science team, or for practitioners interested in the field of data science and machine learning. These articles (and more) will soon be combined in several booklets available exclusively for…

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Added by Vincent Granville on April 14, 2018 at 11:00am — No Comments

Weekly Digest, April 16

Monday newsletter published by Data Science Central. Previous editions can be found here.  The contribution flagged with a + is our selection for the picture of the week.

Announcements
  • Optimize your career with UVA’s M.S. in Business Analytics. In just twelve months, you’ll develop the skills you need to leverage analytics and drive…
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Added by Vincent Granville on April 14, 2018 at 9:00am — No Comments

Technical Boundary Analysis

About a month ago, I posted a blog on “Technical Deconstruction.” I described this as a technique to break down aggregate data to distinguish between its contributing parts: these parts might contain unique characteristics compared to the aggregate.  For instance, I suggested that it can be helpful to break down data by workday - that is to say, maintaining separate data for each day of the week.  I said that the data could be further deconstructed perhaps by time period and employee: the…

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Added by Don Philip Faithful on April 14, 2018 at 8:00am — No Comments

Simple Trick to Prevent Cambridge Analytica and Others to Hack into Facebook Data

Cambridge Analytica was caught tampering with elections by exploiting Facebook, but chances are that this is the tip of the iceberg, and that many others, including scammers and ID thieves, are also exploiting Facebook and other social networks. One way that they do this is as follows.

Cambridge Analytica website (front page) -…

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Added by Vincent Granville on April 14, 2018 at 7:30am — No Comments

Tutorial: Multistep Forecasting with Seasonal ARIMA in Python

When trend and seasonality is present in a time series, instead of decomposing it manually to fit an ARMA model using the Box Jenkins method, another very popular method is to use the seasonal autoregressive integrated moving average (SARIMA) model which is a generalization of an ARMA model. SARIMA models are denoted SARIMA(p,d,q)(P,D,Q)[S], where S refers to the number of periods in each season, d is the degree of differencing (the number of times the…

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Added by Kostas Hatalis on April 12, 2018 at 10:30am — 1 Comment

Book: Blockchain Basics: A Non-Technical Introduction in 25 Steps

In 25 concise steps, you will learn the basics of blockchain technology. No mathematical formulas, program code, or computer science jargon are used. No previous knowledge in computer science, mathematics, programming, or cryptography is required. Terminology is explained through pictures, analogies, and metaphors.

This book bridges the gap that exists between purely technical books about the blockchain and purely business-focused books. It does so by explaining both the technical…

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Added by Capri Granville on April 12, 2018 at 6:30am — 1 Comment

Thursday News: Blockchain, IoT, AI, ML, Python, Neural Networks, NLP

Here is our selection of featured article posted since Monday:

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Added by Vincent Granville on April 12, 2018 at 6:30am — No Comments

Machine Learning with Signal Processing Techniques

Stochastic Signal Analysis is a field of science concerned with the processing, modification and analysis of (stochastic) signals.

Anyone with a background in Physics or Engineering knows to some degree about signal analysis techniques, what these technique are and how they can be used to analyze, model and classify signals.

Data Scientists coming from a different fields, like Computer Science or Statistics, might not be aware of the analytical power these techniques bring with…

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Added by Ahmet Taspinar on April 12, 2018 at 6:00am — No Comments

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