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April 2016 Blog Posts (86)

12 Python Resources for Data Science

About 8,300 articles related to Python have been posted on Data Science Central, according to Google. Below is a small sample -- the 12 most useful and popular articles to get started with Python and data science.  The Guide to Learning Python for Data Science has been moved…

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Added by Vincent Granville on April 21, 2016 at 8:30am — No Comments

Automated Predictive Analytics – What Could Possibly Go Wrong?

Summary:  Will Automated Predictive Analytics be a boon to professional data scientists or a dangerous diversion allowing well-meaning, motivated but amateur users try to implement predictive analytics.  More on the conversation started last week about new One-Click Data-In Model-Out platforms.

 

I have always been very much of…

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Added by William Vorhies on April 20, 2016 at 10:21am — 2 Comments

Weekly Digest, April 25

Starred articles are new additions posted between Thursday and Sunday, published in the Monday edition exclusively. The Monday edition 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 Thursday edition covers articles published between Monday and Wednesday.

The …

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Added by Vincent Granville on April 20, 2016 at 10:00am — No Comments

Maximizing Data Value with a Data Lake

Contributed by Chuck Currin of Mather Economics:

There’s tremendous value in corporate data, and some companies can maximize their data value through the use of a data lake. This assumes that the adopting company has high volume, unstructured data to contend with. The following article describes ways that a data lake can help companies maximize the value of their data. The term “data lake” has been credited to…

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Added by Lisa Hester on April 20, 2016 at 8:22am — 4 Comments

Machine Learning Ontology

Instead of seeing each Machine Learning (ML) method as a “shiny new object”, here is an attempt to create a unified picture. There is no consensus when it comes to an ontology for ML methods; organizational principles are simply ways to get our arms around knowledge so that we are not swamped by too many unconnected notions.

 

A powerful organization of the concepts or Ontology of ML is based on conditional expectation.

 

Conditional…

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Added by PG Madhavan on April 20, 2016 at 6:11am — 1 Comment

How to improve your online KPIs – Part 1. Know your Demand

As a follow-up to my previous post "Using Machine Learning to predict Customer Behaviour", I wanted to address a similar topic but from an e-commerce perspective. How to you predict the behaviour of your visitors in your online store? and more importantly, how do you leverage this knowledge in order to optimize your traffic, conversion, profit, or whatever KPI…

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Added by Alex Marandon on April 19, 2016 at 11:40pm — No Comments

Random-ized Forest: A new class of Ensemble algorithms

Originally posted on :Linkedin

It's a known fact that bagging (an ensemble technique) works well on unstable algorithms like decision trees, artificial neural networks and not on stable algorithms like Naive Bayes. The well known…

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Added by Ashish kumar on April 19, 2016 at 1:30pm — No Comments

20 Data Science and Mathematical Challenges

I invite you to solve these challenges yourself before reading the solutions (for some of these problems) or hints to help you tackle these problems.

  1. Interesting Recursive Formula
  2. Identifying patterns in…
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Added by Vincent Granville on April 19, 2016 at 9:44am — No Comments

Answers to dozens of data science job interview questions

We just started in this article to provide answers to one of the largest collection of data science job interview questions ever published, and we will continue to add answers to most of these questions. Some answers link to solutions offered in my Wiley data science book: you can find this book here. The 91 job interview questions were originally published…

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Added by Vincent Granville on April 19, 2016 at 9:12am — No Comments

Industrialising Data Science

The application of pattern recognition technology to large datasets has revolutionised the digital economy. But digital represents only 5% of GDP in OECD countries: the remaining 95% is still largely untouched by data science (DS). The larger “old economy” companies are just beginning their data journey and data science is yet to be institutionalised: Outside the tech leviathans DS is still a cottage industry with artisan DS crafting bespoke prototypes to their own…

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Added by Harry Powell on April 19, 2016 at 7:41am — 5 Comments

50 Shades of Grey – The Psychology of a Data Scientist

Unless you’ve recently graduated from one of the new Data Science courses that have been popping up online and in various universities around the world, then becoming a Data Scientist was most likely slightly accidental and was more about the journey than the destination.

 

Here’s my journey. See if you recognise any of it in your own:

I started out as a physicist and had a strong mathematical grounding, but I had a passion for medicine. After completing my bachelor’s…

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Added by Lee Baker on April 19, 2016 at 2:00am — 6 Comments

Could your algorithm win $50,000?

A world-class mathematical challenge and a chance to win $50,000 AUD



The Unearthed Phase-X Challenge, in partnership with BHP Billiton, is open to university students and research institutes around the world to devise an innovative and efficient solution to a defined challenge in open pit mining.



Participants will be given access to multiple sets of BHP Billiton’s operational data and asked to apply their mathematical minds to create the best…

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Added by Justin Strharsky on April 18, 2016 at 11:51pm — No Comments

Searching Google for Images Similar to a Specific Image

You can search Google for pictures similar to a given image, for plagiarism detection or to find people that look like you. 

Here's how I did a test:

  • I used the Search by Image tool from Google
  • I chose the option Upload an image
  • I used a screenshot tool, to extract a picture of myself, free of compromising metadata (see figure 1 and 3), then clicked on the picture icon in the Google search box to…
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Added by Vincent Granville on April 18, 2016 at 6:00pm — 1 Comment

Critical Skills to Bridge the Gap Between Software Development and Data Science

Software Development and Data Science



While on the job, data scientists are often required to perform a large set of tasks that they are taught how to do through their education and formal training. Despite this, many data scientists are not taught the fundamental aspects of software…

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Added by Jennifer Livingston on April 18, 2016 at 9:00am — No Comments

Talent Analytics…Does Maturity Really Matter?

This article was written by Sara Roberts. As Co-Founder and Principal Consultant at Category One Consulting (C1C), Sara is committed to helping organizations maximize their people and program effectiveness through the application of research, analytics, and evidence-based practice.

Organizations have understood the importance of using data to inform financial, sales, and marketing decisions for quite some time; however, this data-driven focus has only recently extended itself…

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Added by Emmanuelle Rieuf on April 18, 2016 at 7:30am — No Comments

How Big Data is Changing the Games We Love

You’ll be hard pressed to find any industry that big data hasn’t touched in one way or another. And if you look at sports – and professional sports in particular – it’s clear that big data and the games we all know and love are closely interconnected. From coaches and players to fans and trainers, the people in and around these games now have access to technologies that weren’t even a thought in the past.

4 Specific Ways Big Data is Impacting…

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Added by Larry Alton on April 18, 2016 at 5:50am — 1 Comment

How Data Security Can Protect Your Business

For the past years, one of the main concerns of businesses and consumers is data security. As technology progresses, digital thieves have become more persistent in staging their attacks to gain unauthorized access to personal information, financial records, intellectual property, and other valuable data.

 

Over the…

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Added by Micah De Jesus on April 18, 2016 at 12:30am — No Comments

40 Interview Questions asked at Startups in Machine Learning / Data Science

This article was posted by Manish Saraswat on Analytics Vidhya. Manish who works in marketing and Data Science at Analytics Vidhya believes that education can change this world. R, Data Science and Machine Learning keep him busy.

Machine learning and data science are being looked as the drivers of the next industrial revolution happening in the world today. This also means that there are numerous …

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Added by Emmanuelle Rieuf on April 16, 2016 at 1:00pm — No Comments

Palming off the Earth: Data, Code, Analysis

Contributed by Wanda Wang. She  is currently in the NYC Data Science Academy …

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Added by NYC Data Science Academy on April 16, 2016 at 9:30am — No Comments

Feature engineering for building clustering models

We frequently get questions about whether we have chosen all the right parameters to build a machine learning model. There are two scenarios: either we have sufficient attributes (or variables) and we need to select the best ones OR we have only a handful of attributes and we need to know if these are impactful. Both are classic examples of feature engineering challenges

Most of the…

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Added by BR Deshpande on April 16, 2016 at 9:00am — No Comments

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