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8 Best Practices to Maximize ROI from Predictive Analytics - Analytics.CLUB

Back in 2010, Forbes.com forecasted that something new and interesting called predictive analytics was emerging as a “game changer.” Well, fast …

Key tools of Big Data for Transformation: Review & Case Study

Guest blog post by Syed Danish Ali<p><b>Review</b><p>The challenges of big data can be captured succinctly as follows[1],[2]:<p>Volume; ever increasing volume which …

An Introduction to Model-Based Machine Learning

This guest post was written by Daniel Emaasit, a Ph.D Student of Transportation Engineering at the University of Nevada, Las Vegas. Daniel’s research …

Machine Learning

Big Data Trends: 38 Top Experts on the Biggest Trends

You know it.<p>As we speak, big data is transforming businesses and our very lives.<p>But exactly how? What are the key trends in big data that are changing how we work?<p>Which of these trends are your competitors leveraging to get an edge in the industry?<p><b>We asked one question to 38 well known experts in</b> …

Data is Banking's Most Powerful Competitive Weapon

The financial services industry's most significant competitive advantage is the customer insights that can be extracted from data. The key is using …

Improving quality of life with Spark-empowered machine learning

Machine learning is finding its way into a variety of applications. Discover an open source machine learning platform that combines the data …

Machine Learning

Reporting versus analytics

<i>“We are drowning in information but starved for knowledge.”</i><p><i>- John Naisbitt</i><p>For the love of statistics, please stop using the words “reporting” and …

Feather: fast, interoperable data import/export for R

Unlike most other statistical software packages, R doesn't have a native data file format. You can certainly import and export data in any number of …

Python Programming

A Refresher on Statistical Significance

When you run an experiment or analyze data, you want to know if your findings are “significant.” But business relevance (i.e., practical significance) isn’t always the same thing as confidence that a result isn’t due purely to chance (i.e., statistical significance). This is an important …

Parallel_Processing_in_Python

Parallel Processing in Python¶<p>author: Jacob Schreiber<br>contact: jmschr@cs.washington.edu<p>Simply put, parallel processing is splitting up a task between …

Chief Scientist At 1-Page Reveals How To Get Started In Machine Learning

<i>What would be your advice to a software engineer who wants to learn machine learning? originally appeared on Quora - the knowledge sharing network where compelling questions are answered by people with unique insights.</i><p><b>Answer by Alex Smola, Professor, Carnegie Mellon University and Chief Scientist,</b> …

The Tools of Big Data Science: The Technologies & Languages of Statistical Analysis

You’ve read about many of the kinds of big data projects that you can use to learn more about your data in our What Can a Data Scientist Do for You? …

Big Data

A gentle introduction to parallel computing in R

by John Mount Ph.D.<br>Data Scientist at Win-Vector LLC<p>Let's talk about the use and benefits of parallel computation in R.<p>Parallel computing is a type of …

TOP SECRET: Newly declassified documents on evaluating models based on predictive accuracy | StatsBlogs.com | All About Statistics

(This article was originally published at Statistical Modeling, Causal Inference, and Social Science, and syndicated at StatsBlogs.)<p>We recently had …

Three things I wish I knew earlier about Machine Learning

I’ve been working with Machine Learning models both in academic and industrial settings for a few years now. I’ve recently been watching the …

Machine Learning

Food for your health.

Gifting is without a doubt a craftsmanship and it is very imperative to include some innovativeness with a sprinkle of adoration in the way you …

Dessert

SAS Blogs

What if a famous soccer team asks you to predict how many tickets for their next match will be sold to women? Seventy students from Bicocca …

Machine Learning

A tiny multi threaded job queue in 30 lines of python

Recently while plotting some data while doing gradient descent on my neural net, i ran across some performance issues. My gradient descent code was …

16 case studies of companies proving ROI of Big Data

Big Data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. Challenges include analysis, …

Big Data

Quantifying the Impact of Marketing Analytics

Marketing analytics is becoming big business. With the promise of improved precision and performance, advanced analytics and Big Data have set off something of a buying frenzy.<p>Companies currently spend 6.7% of their marketing budgets on analytics and expect to spend 11.1% over the next three years, …

Redirecting...

15 Mathematics MOOCs for Data Science

Most of the mathematics required for Data Science lie within the realms of statistics and algebra, which explains the disproportionate number of …

Data Science

Python for Data Science For Dummies Cheat Sheet - dummies

Python is an incredible programming language that you can use to perform data science tasks with minimal effort. The huge number of available …

Python Programming

INSIGHT: Why Big Data isn’t suited to analytics

Big Data is not intrinsically suited to analytics. I’m sorry, but it’s true.<p>Distributed storage and massive scale can make data hard to find. Lack of …

Big Data

Jupyter Notebook Viewer

Introduction to Data Analysis with Python<p>Dr. Thomas Wiecki<p>Lead Data Scientist<p>Introduction to Data Analysis with Python<p>The Path of the PyData Ninja<p>Dr. …

Hedge Funds

When Big Data becomes bad data: The limits of analytics

Corporations are increasingly using algorithms to make business decisions, raising a host of new legal questions<p>A recent ProPublica analysis of The Princeton Review’s prices for online SAT tutoring shows that customers in areas with a high density of Asian residents are often charged more. When …

A Complete Tutorial on Tree Based Modeling from Scratch (in R Python)

Introduction<p>Tree based learning algorithms are considered to be one of the best and mostly used supervised learning methods. Tree based methods …

Data Science with Python & R: Dimensionality Reduction and Clustering

20 Best Free Tutorials to Learn Python: Find the Killer Python Tutorial PDF, eBook or Online

Python is one of the most elegant and complete programming language and comes packed with tons of features to develop web applications as well as …

Python Programming

5 New R Packages for Data Scientists

by Joseph Rickert<p>One great beauty of the R ecosystem, and perhaps the primary reason for R’s phenomenal growth, is the system for contributing new …