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Featured Blog Posts – April 2016 Archive (72)

5 Reasons you should take part in Hackathons

Data is growing, and hence is the requirement for perfect decision making by companies. In this era where analytics is the new buzzword, companies are looking for able and determined Data Scientists.

But as always, the quest to get the sexiest and the highest paying job is not an easy task. For acquiring such a demanding position one must be well skilled and experienced.

Don’t freak out! Because now a days a lot of resources and tips are available to be perfect in what you are…

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Added by Sukanya Mohapatra on April 15, 2016 at 4:30am — No Comments

Weekly Digest, April 18

Starred articles are new additions or updated content, posted between Thursday and Sunday. The weekly digest has six sections: (1) Featured Resources and Technical Contributions, (2) Featured Articles and Case Studies, (3) From our Sponsors, (4) News, Events, Books, Training, Forum Questions, (5) Picture of the Week, and (6) Syndicated Content.

The full version is always published Monday.…

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Added by Vincent Granville on April 13, 2016 at 9:30am — No Comments

Data Scientists Automated and Unemployed by 2025!

Summary:  The shortage of data scientists is driving a growing number of developers to fully Automated Predictive Analytic platforms.  Some of these offer true One-Click Data-In-Model-Out capability, playing to Citizen Data Scientists with limited or no data science expertise.  Who are these players and what does it mean for the profession of data science?

 …

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Added by William Vorhies on April 13, 2016 at 8:30am — 8 Comments

10 Deep Learning Terms Explained in Simple English

 

Deep Learning is a new area of Machine Learning research that has been gaining significant media interest owing to the role it is playing in artificial intelligence applications like image recognition, self-driving cars and most recently the AlphaGo vs. Lee Sedol matches. Recently, Deep Learning techniques have become…

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Added by Mike Waldron on April 11, 2016 at 6:30am — 3 Comments

How to Treat Missing Values in Your Data

One of most excruciating pain points during Data Exploration and Preparation stage of an Analytics project are missing values.

How do you deal with missing values - ignore or treat them? The answer would depend on the percentage of those missing values in the dataset, the variables affected by missing values, whether those missing values are a part of dependent or the independent variables, etc. Missing Value treatment becomes important since the data insights or the…

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Added by Jacob Joseph on April 11, 2016 at 3:30am — 5 Comments

Using Machine Learning to Predict Customer Behaviour

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Added by Alex Marandon on April 10, 2016 at 10:47pm — 3 Comments

Can DeepMind win 'Jeopardy' and Watson win 'Go'?

original Post: linkedin

We are indeed living in interesting times, where we celebrate human-built machines defeating the best human minds at variety of activities. IBM Deep Blue's win against Chess champ…

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Added by Ashish kumar on April 10, 2016 at 10:24am — No Comments

TUPAQ - Automating Model Search for Large Scale Machine Learning

Simplifying and automating machine learning processes and techniques - that depend on large-scale, distributed datasets to achieve high statistical performance - is critical for the future of applied data science.…
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Added by Michael Walker on April 9, 2016 at 9:00am — No Comments

Role of Attribution Modelling in the Analysis of Codified Narrative

In this blog, I will be discussing the use of attribution models in relation to codified narrative. For this purpose, I will be referring to the plots of two films: the 1974 horror classic “The Texas Chainsaw Massacre”; and a 2014 dark comedy called “Tusk.” I have my own codification system called BERLIN: this is short for “Behavioural Event Reconstruction Linguistic Interface for Narratives.” An attribution model supports the inference of meaning from data. Imagine a student one day going…

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Added by Don Philip Faithful on April 9, 2016 at 7:08am — No Comments

Outlier Detection with Parametric and Non-Parametric methods

Dealing with Outliers is like searching a needle in a haystack

This is a guest…

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Added by Jacob Joseph on April 8, 2016 at 2:30am — 5 Comments

Introduction to Machine Learning / Data Mining

Machine Learning? Data Mining?



Well, there is a little bit difference between machine learning and data mining although I don't see any difference between them.

See the Stackexchange debate on the difference between machine learning and data mining.



At the end, it is about training the machine to…

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Added by Gregory Choi on April 7, 2016 at 4:30pm — No Comments

The Panama Papers – how did they pull off history’s biggest data leak?

Find out how Data to Value’s Graph Data software partners Neo4j and Linkurious have been used in the Panama Papers investigation.

Recently there has been a lot of interest around the newly published Panama papers. This giant trove of data that is said to contain a whopping 11.5 million documents or…

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Added by Zygimantas Jacikevicius on April 7, 2016 at 4:59am — No Comments

5 Dangers of Ignoring Data as a Modern Business

For a modern business, data is everything. It can tell you who your customers are, what they like best, what ideas you should pursue, and how those ideas will eventually perform. If you can ask the right questions and use the right tools to uncover and crunch the data, you’ll be in a much better position to sustain your profitability and outcompete your rival businesses.

The Ignorance of Data

The problem is, many businesses are ignoring data, or neglecting it in crucial…

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Added by Larry Alton on April 7, 2016 at 2:24am — 1 Comment

Weekly Digest, April 11

Starred articles are new additions or updated content, posted between Thursday and Sunday. The weekly digest has six sections: (1) Featured Resources and Technical Contributions, (2) Featured Articles and Case Studies, (3) From our Sponsors, (4) News, Events, Books, Training, Forum Questions, (5) Picture of the Week, and (6) Syndicated Content.

The full version is always published Monday.…

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Added by Vincent Granville on April 6, 2016 at 2:30pm — No Comments

Healthcare BI Platform Market to Grow

A business intelligence platform is used by healthcare organizations to build helpful healthcare applications that assist them in ensuring the provision of quality healthcare to patients. BI platforms help control healthcare costs and provide several benefits to healthcare organizations such as analysis capability, providing information on delivery, and integration. 

Healthcare BI platforms offer a very useful function called financial analytics. The availability of the financial…

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Added by Ankit Jain on April 6, 2016 at 10:30am — No Comments

Analytics in E-commerce industry

The E-Commerce boon didn’t just change the way we buy goods, it revolutionized the way we look at our customers completely. E-Commerce uses analytics as a tool to study consumer behavior further boosting sales, acquiring new customers and building a brand. There are 4 major heads in any e-commerce business that need to be analyzed to ensure proper functioning of the business:

  1. As most of the commerce businesses just act as a platform to connect buyers…
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Added by Tanmay Bhandari on April 6, 2016 at 10:00am — No Comments

3 Trends in Data Storytelling

Data storytelling is undergoing a big change, one that will influence not only data journalism but also how data is shown in the business world. And 2016 will only accelerate this trend.

Five years ago, data journalism focused on rich interactives designed primarily for a monitor or laptop screen. Those interactives were complete applications, destinations to be browsed. You could explore, drill down, filter, and play with them. This was a rich experience in the days when we used a…

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Added by Andy Cotgreave on April 6, 2016 at 9:26am — No Comments

R tutorial (R programming basic 101)

[The goal of this page]

When I have read all R introductions, the books were filled with just instructions. The goal of R is to solve our real life problem. That's why I want to minimize this page. In the real though, we need to understand some key concepts that might be useful for you to tackle the real life problem. Here's basic data structures and data manipulation method.



Still, I believe the best way to learn R programming language is to tackle the real life…

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Added by Gregory Choi on April 6, 2016 at 8:53am — 4 Comments

The Data Quality Tipping Point

Whatever your business sector, data is your most valuable asset. Along with the machinery and stock you hold, data and insights hold the key to profit and growth. But it has the unique ability to unite every department, and every function. It can reveal problems in processes, drive productivity among your staff and ensure everyone is ‘singing from the same hymn…

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Added by Martin Doyle on April 6, 2016 at 3:30am — No Comments

Must Know Tips/Tricks in Deep Neural Networks

Guest blog post by Xiu-Shen Wei, originally posted here

Deep Neural Networks, especially Convolutional Neural Networks (CNN), allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods…

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Added by Vincent Granville on April 5, 2016 at 4:00pm — No Comments

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