# Tag: Data Analysis

**Tidyverse, an opinionated Data Science Toolbox in R from Hadley Wickham**- Oct 10, 2017.

Get your productivity boosted with Hadley Wickham's powerful R library, Tidyverse. It has all you need to start developing your own data science workflows.**Big Data or Big BS?**- Sep 7, 2017.

Data and analysis of data have, in some form, been used to aid decision making since ancient times. So why, after all these centuries are data and analytics not more embedded in corporate decision making?**A Guide to Instagramming with Python for Data Analysis**- Aug 17, 2017.

I am writing this article to show you the basics of using Instagram in a programmatic way. You can benefit from this if you want to use it in a data analysis, computer vision, or any other cool project you can think of.**How to squeeze the most from your training data**- Jul 27, 2017.

In many cases, getting enough well-labelled training data is a huge hurdle for developing accurate prediction systems. Here is an innovative approach which uses SVM to get the most from training data.**The BI & Data Analysis Conundrum: 8 Reasons Why Many Big Data Analytics Solutions Fail to Deliver Value**- Jul 26, 2017.

Why many BI & Analytics projects/solutions fail to deliver the business value? Let’s find out the answers to such questions.**The Guerrilla Guide to Machine Learning with Julia**- Jul 12, 2017.

This post is a lean look at learning machine learning with Julia. It is a complete, if very short, course for the quick study hacker with no time (or patience) to spare.**Exploratory Data Analysis in Python**- Jul 7, 2017.

We view EDA very much like a tree: there is a basic series of steps you perform every time you perform EDA (the main trunk of the tree) but at each step, observations will lead you down other avenues (branches) of exploration by raising questions you want to answer or hypotheses you want to test.**Getting Started with Python for Data Analysis**- Jul 5, 2017.

A guide for beginners to Python for getting started with data analysis.

**Will Apache Spark Finally Advance Genomic Data Analysis?**- Jun 23, 2017.

Spark has been useful in mapping out genetic traits that can be associated with certain diseases and the genetic makeup of microorganisms that live in our bodies.**K-means Clustering with Tableau – Call Detail Records Example**- Jun 16, 2017.

We show how to use Tableau 10 clustering feature to create statistically-based segments that provide insights about similarities in different groups and performance of the groups when compared to each other.**K-means Clustering with R: Call Detail Record Analysis**- Jun 6, 2017.

Call Detail Record (CDR) is the information captured by the telecom companies during Call, SMS, and Internet activity of a customer. This information provides greater insights about the customer’s needs when used with customer demographics.**The Guerrilla Guide to Machine Learning with R**- May 11, 2017.

This post is a lean look at learning machine learning with R. It is a complete, if very short, course for the quick study hacker with no time (or patience) to spare.**Technically Speaking – Analytic solutions to real-world problems**- May 3, 2017.

Are you and your data "having issues?" JMP real-world case studies help you solve them with key insights on overcoming the challenges with data collection, preparation, and analysis.**Did you know cavemen were already dealing with “Big Data” issues?**- May 3, 2017.

We know Big Data & Analytics are new & cutting edge technologies; but actually, human started using data & analytics techniques 5000 years ago. Let’s take a look.**The Value of Exploratory Data Analysis**- Apr 20, 2017.

In this post, we will give a high level overview of what exploratory data analysis (EDA) typically entails and then describe three of the major ways EDA is critical to successfully model and interpret its results.**What is Structural Equation Modeling?**- Mar 27, 2017.

Structural Equation Modeling (SEM) is an extremely broad and flexible framework for data analysis, perhaps better thought of as a family of related methods rather than as a single technique. What is its relevance to Marketing Research?**Time Series Analysis: A Primer**- Jan 17, 2017.

Time series analysis is a complex subject but, in short, when we use our usual cross-sectional techniques such as regression on time series data, variables can appear "more significant" than they really are and we are not taking advantage of the information the serial correlation in the data provides.**Over 600 data science, machine learning, Big Data eBooks/videos for only $5 (until Jan 9)**- Dec 22, 2016.

Packt have more than 600 data science, analysis, machine learning and Big Data eBooks and video courses. And until Jan 9, 2017 every single one is available for just $5.**Free ebooks: Machine Learning with Python and Practical Data Analysis**- Dec 5, 2016.

Two free ebooks: "Building Machine Learning Systems with Python" and "Practical Data Analysis" will give your skills a boost and make a great start in the New Year.**Behind the Dream of Data Work as it Could Be**- Sep 13, 2016.

This post is an insider's overview of data.world, and their attempt to build the most meaningful, collaborative, and abundant data resource in the world.**Top KDnuggets tweets, Jul 6 – Jul 12: Statistical Data Analysis #Python #Jupyter Notebooks; Modern Pandas Notebooks**- Jul 13, 2016.

Statistical Data Analysis in #Python (#Jupyter Notebooks); Modern Pandas: idiomatic Pandas notebook collection; New (free) book by @rdpeng: #rstats Programming for #DataScience**Webinar, Jun 30: Introducing Anaconda Mosaic: Visualize. Explore. Transform. Once and Done**- Jun 28, 2016.

On June 30th, Continuum Analytics Product Manager Lance Ransom will showcase how Anaconda Mosaic can empower your organization to light up your dark data. Save your spot now!**Comprehensive Guide to Learning Python for Data Analysis and Data Science**- Apr 20, 2016.

Want to make a career change to Data Science using python? Well learning anything on your own can be a challenge & a little guidance could be a great help, that is exactly what this article will provide you with.**Integrating Python and R into a Data Analysis Pipeline, Part 1**- Oct 29, 2015.

The first in a series of blog posts that: outline the basic strategy for integrating Python and R, run through the different steps involved in this process; and give a real example of how and why you would want to do this.**Which Movie Sequels Are Really Better? A Data Science Answer**- Oct 19, 2015.

The internet is filled with polls and lists of sequels that are better or worse movie in the series. Yet such rankings are often based on personal judgement and rarely on data and statistics. Here is our solution to analyze and visualize the movie series.**Statistics – Understanding the Levels of Measurement**- Aug 6, 2015.

For doing statistics or analytics it is first step to understand the variables. Moreover, it is important that one truly knows which measure to take with different available types.**Statistics Denial Myth: Repackaging Statistics With Straddling Terms**- Jul 16, 2015.

Data science is nothing but the old wine in new bottle versions of the statistics with different fields. Here, we are busting the myth which states data scientist is new and different than traditional statisticians.**I’m a data scientist – mind if I do surgery on your heart?**- Jun 18, 2015.

If I walked into an operating room and said I'm going to start dabbling in surgery I would be immediately thrown out. But people do that with statistics and data analysis all the time.**Interview: David Kasik, Boeing on Data Analysis vs Data Analytics**- Feb 23, 2015.

We discuss the impact of increasing amount of data on visualization, difference between Data Analysis and Data Analytics, motivation, trends, desired skills and more.**Interview: Anthony Bak, Ayasdi on Managing Data Complexity through Topology**- Jan 28, 2015.

We discuss the definition of Topology, its relevance to Big Data and compare Topological Data Analysis (TDA) with other approaches.**8 Things to Check when you analyze Twitter data**- Dec 16, 2014.

A review of biases and issues on large scale studies of human behavior in social media discussed by a recent paper published on Science.**ASE International Conference on Big Data Science 2014: Day 4 Highlights**- Aug 8, 2014.

Highlights from the presentations by Data Science leaders from UC Berkeley, Clark Atlanta Univ, Florida Institute of Technology, Rober Bosh LLC and HP on day 4 of ASE Conference on Big Data Science 2014, Stanford.**Manufacturing Analytics Summit 2014 Chicago: Day 2 Highlights**- Jul 17, 2014.

Highlights from the presentations by Analytics leaders from World Fuel Services, Vigilent Corporation, Caterpillar and SunEdison on day 2 of Manufacturing Analytics Summit 2014 in Chicago.**Manufacturing Analytics Summit 2014 Chicago: Day 1 Highlights**- Jul 14, 2014.

Highlights from the presentations by Analytics leaders from McCormick, HP, Patheon and Boeing on day 1 of Manufacturing Analytics Summit 2014 in Chicago.**Domino – A Platform For Modern Data Analysis**- Jun 26, 2014.

Tools that facilitate data science best practices have not yet matured to match their counterparts in the world of software engineering. Domino is a platform built from the ground up to fill in these gaps and accelerate modern analytical workflows.**Top KDnuggets tweets, Jun 13-15: Book: Data Classification: Algorithms and Applications**- Jun 16, 2014.

Book: Data Classification: Algorithms and Applications; Top 10 Data Analysis Tools for Business; #BigData companies to watch selected by top analytics experts; The Cardinal Sin of Data Mining and Data Science: Overfitting.**Top 10 Data Analysis Tools for Business**- Jun 13, 2014.

Ten free, easy-to-use, and powerful tools to help you analyze and visualize data, analyze social networks, do optimization, search more efficiently, and solve your data analysis problems.