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A Comprehensive Guide to Data Exploration

A Comprehensive Guide to Data Exploration | Analytics | Scoop.it
Here's a tutorial on data exploration which comprises of missing value imputation, outlier removal, feature engineering, variable creation
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A Look at Text Analytics

A Look at Text Analytics | Analytics | Scoop.it
Mining for Gold The first step in text analytics is text mining―the process of determining and collecting high-quality information from unstructured text. The very first step of text mining is
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Proc DS2 – First Impressions | Zencos

Proc DS2 – First Impressions | Zencos | Analytics | Scoop.it
Zencos develops business intelligence (BI) solutions for Fortune 1000 companies. We provide strategy, architecture, implementation, and administration & support services. Our industry expertise includes media & entertainment, financial services, digital media, state and local government and healthcare.
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38 great resources for learning data mining concepts and techniques

38 great resources for learning data mining concepts and techniques | Analytics | Scoop.it
In the blossoming world of Big Data, the data miner is king. 

With today’s tools, anyone can collect data from almost anywhere, but not
everyone can pull the important nuggets out of that data. Whacking your
data into Tableau is an OK start, but it’s not going to give you the
business critical insights you’re looking for. To truly make your data come
alive you need to mine it. Dig deep. Play around. And tease out the diamond
in the rough.

Jumpstarting your data mining journey can be an uphill battle if you didn’t
study data science in school. Not to worry! Few of today’s brightest data
scientists did. So, for those of us who may need a little refresher on data
mining or are starting from scratch, here are 38 great resources to learn
data mining concepts and techniques.
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18 Useful Mobile Apps for Data Scientist / Data Analysts

18 Useful Mobile Apps for Data Scientist / Data Analysts | Analytics | Scoop.it
Here are 18 useful android mobile apps recommended for data scientist data analyst to improve their cognitive logical mathematical skills
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Analytics-as-a-Service: Understanding how Amazon.com is changing the rules

Analytics-as-a-Service:  Understanding how Amazon.com is changing the rules | Analytics | Scoop.it

“By 2014, 30% of analytic applications will use proactive, predictive and forecasting capabilities” 


Via Carlos Lizarraga Celaya
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Carlos Lizarraga Celaya's curator insight, December 3, 2015 6:26 PM

Gartner Forecast "More firms will adopt Amazon EC2 or EMR or Google App Engine "platforms for data analytics. Put in a credit card, by an hour or months worth of compute and storage data. Charge for what you use. No sign up period or fee. Ability to fire up complex analytic systems. Can be a small or large player”

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13 Tips to make you awesome in Data Science / Analytics Jobs

13 Tips to make you awesome in Data Science / Analytics Jobs | Analytics | Scoop.it
Here are some tips to help you perform better at data science / analytics jobs in your company. successful data scientists follow these tips
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20 short tutorials all data scientists should read (and practice) - Data Science Central

20 short tutorials all data scientists should read (and practice) - Data Science Central | Analytics | Scoop.it

The links to core data science concepts are below - I need to add links to web crawling, attribution modeling and API design. Relevancy engines are discussed in some of the tutorials listed below. And that will complete my 10-page cheat sheet for data science.


Via Carlos Lizarraga Celaya
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How to create compelling analytical stories using infographics?

How to create compelling analytical stories using infographics? | Analytics | Scoop.it
Infographics are graphic visual representations of information, data, knowledge intended to present complex information quickly, clearly. Article explains process too.
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The Hackathon Practice Guide by Analytics Vidhya

The Hackathon Practice Guide by Analytics Vidhya | Analytics | Scoop.it
Resource and guide to learn python, R, and the overview of logistic regression, decision tree, SVM, hypothesis generation, data exploration, random forest and prepare for Data Hackathon Online Contest.
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The Hackathon Practice Guide by Analytics Vidhya

The Hackathon Practice Guide by Analytics Vidhya | Analytics | Scoop.it
Resource to learn python, R, and the overview of logistic regression, decision tree, SVM, hypothesis generation, data exploration, random forest
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Descriptive statistics—the more, the merrier in SAS Visual Analytics

Descriptive statistics—the more, the merrier in SAS Visual Analytics | Analytics | Scoop.it
This blog is not about the original movie The More the Merrier (1943) or its remake, Walk, Don’t Run (1966), which I’ve actually seen a couple of times.
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How to detect Outliers in your dataset and treat them?

How to detect Outliers in your dataset and treat them? | Analytics | Scoop.it
Finding & treating outliers in your dataset can improve your models & predictions. We explain how to detect & treat outliers in a dataset.
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New Machine Learning Cheat Sheet by Emily Barry

New Machine Learning Cheat Sheet by Emily Barry | Analytics | Scoop.it
This blog about machine learning was written by Emily Barry. Emily is a Data Scientist in San Francisco, California. She really loves emoji. Another thing she…
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Machine Learning and the Great Data Analytics Shake-Up

Machine Learning and the Great Data Analytics Shake-Up | Analytics | Scoop.it
New capabilities of analytics technology and machine learning are providing companies with greater insight and actionable intelligence than ever before.
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Text Mining: What is text mining and how it can be useful in Analytics

Text Mining: What is text mining and how it can be useful in Analytics | Analytics | Scoop.it
Text mining is widely used in the industry when data is unstructured. Derived information can be provided in the form of numbers (indices), categories or clusters, summary of text.
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8 Proven Ways for improving the

8 Proven Ways for improving the | Analytics | Scoop.it
Here are 8 proven ways to improve accuracy of machine learning model which includes cross validation, feature engineering, ensemble & outliers
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7 Hallmarks of a Great Analyst

7 Hallmarks of a Great Analyst | Analytics | Scoop.it
There are lots of analysts. Few good ones – and excellent ones are like hens teeth. Analysts are the interface between data and action – the insight of the organisation. They are important. They can change your strategy. They can leverage and exploit your big data into smart data. They transform data to insight and …
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6 Practices to enhance the performance of a Text Classification Model

6 Practices to enhance the performance of a Text Classification Model | Analytics | Scoop.it
Introduction A few months back, I was working on creating a sentiment classifier for Twitter data. After trying the common approaches, I was still struggling to get good accuracy on the results. Text classification problems and algorithms have been around for a while now. They are widely used for Email Spam Filtering by the likes of
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Perfect way to build a Predictive Model in less than 10 minutes

Perfect way to build a Predictive Model in less than 10 minutes | Analytics | Scoop.it
This article teaches the ways to build a predictive model by saving time during descriptive analytics, data modeling, data treatment analysis
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Exploring the 7 Different Types of Data Stories | MediaShift

Exploring the 7 Different Types of Data Stories | MediaShift | Analytics | Scoop.it
What makes a story truly data-driven? For one, the numbers aren’t caged in a sidebar graph. Instead, the data helps drive the narrative. Data can help narrate as many types of stories as there are angles.
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Top 10 data mining algorithms in plain English | rayli.net

Top 10 data mining algorithms in plain English | rayli.net | Analytics | Scoop.it
Today, I’m going to explain in plain English the top 10 most influential data mining algorithms as voted on by 3 separate panels in this 2007 survey paper.
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5 Steps for Building a Dashboard | Zencos

5 Steps for Building a Dashboard | Zencos | Analytics | Scoop.it
Zencos develops business intelligence (BI) solutions for Fortune 1000 companies. We provide strategy, architecture, implementation, and administration & support services. Our industry expertise includes media & entertainment, financial services, digital media, state and local government and healthcare.
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