This article was posted by Clara Johnson.
Are you trying to find out how to access the dark…Continue
Added by Emmanuelle Rieuf on March 14, 2017 at 9:00am — No Comments
Data science today is a lot like the Wild West: there’s endless opportunity and excitement, but also a lot of chaos and confusion. If you’re new to data science and applied machine learning, evaluating a machine-learning model can seem pretty overwhelming. Now you have help. With this O’Reilly report,…Continue
Added by Emmanuelle Rieuf on March 10, 2017 at 8:00am — No Comments
Added by Emmanuelle Rieuf on March 6, 2017 at 10:30am — No Comments
Long title: The Goal-Question-Metric (GQM) Model to Transform Business Data into an Enterprise Asset.
Today, digitization is dramatically changing the business landscape, and many progressive organizations have started to treat data as a valuable business…Continue
Added by Emmanuelle Rieuf on February 22, 2017 at 12:30pm — No Comments
Python is one of the most powerful, easy-to-read programming languages around, but it does have its limitations. This general purpose, high-level language that can be extended and embedded is a smart option for many programming problems, but a poor solution to…Continue
Added by Emmanuelle Rieuf on February 12, 2017 at 1:30pm — No Comments
This article was written by Jim Frost from Minitab. He came to Minitab with a background in a wide variety of academic research. His role was the “data/stat guy” on research projects that ranged from osteoporosis prevention to quantitative studies of online user behavior. Essentially, his job was to design the appropriate research conditions, accurately generate a vast sea of measurements, and then pull out patterns and meanings from it.
After you have fit a linear model…Continue
Added by Emmanuelle Rieuf on February 11, 2017 at 6:00pm — No Comments
This article was originally posted here, by Mubashir Qasim.
In my last article, I stated that for practitioners (as opposed to theorists), the real prerequisite for machine learning is data analysis, not math.
One of the main reasons for making this statement, is that data scientists spend an inordinate amount of time on data…Continue
This article was written by Yhat.
One of my favorite things about Python is that users get the benefit of observing the R community and then emulating the best parts of it. I'm a big believer that a language is only as helpful as its libraries and…Continue
Added by Emmanuelle Rieuf on February 1, 2017 at 10:00am — No Comments
This article was written by Stephanie and Tony on R2D3.
In machine learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions. Using a data set about homes, we will create a machine learning model to distinguish homes in New York from homes in San Francisco.…Continue
This post was written by Sean Owen.
Data scientists have hundreds of probability distributions from which to choose. Where to start?
Data science, whatever it may be, remains a big deal. “A data scientist is better at…Continue
This article was written by Kris Hammond.
This is an invitation to collaborate. In particular, it is an invitation to collaborate in framing how we look at and develop machine intelligence. Even more specifically, it is an invitation to collaborate in the construction of a Periodic Table of AI.
Let’s be honest. Thinking about Artificial Intelligence has proven to be difficult for us. We argue constantly about what is and is not AI. We…
This article was posted by Arpan Gupta (Indian Institute of Technology).
Let’s learn from a precise demo on Fitting Logistic Regression on Titanic Data Set for Machine Learning
Description:On April 15, 1912, the Titanic sank after…Continue
Added by Emmanuelle Rieuf on January 16, 2017 at 11:00am — No Comments
This article was posted by Ankit Gupta.
If there is one language, every data science professional should know – it is SQL. SQL stands for Structured Query Language. It is a programming language used to access data from relational databases.
We conducted a skilltest to test our community on SQL and it gave 2017 a kicking start. A total of 1666 participants registered for the skilltest.
Jupyter notebook content for my OReilly book, the Python Data Science Handbook.
This repository contains the full listing of IPython notebooks used to create the book, including all text and code. The code was written and tested with Python 3.5, though most (but not all) snippets will work correctly in Python 2.7.
See also the free companion project, …Continue
Added by Emmanuelle Rieuf on January 7, 2017 at 10:00am — No Comments
This article was posted by David Smith on revolution analytics.
IEEE Spectrum has just published its third annual ranking with its 2016 Top Programming Languages, and the R Language is once again near the top of the list, moving up one place to fifth position.…Continue
This announcement was published by the American Statistical Association.
The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for un- dergraduate programs in data science. The group consisted of 25 un- dergraduate faculty from a…
Added by Emmanuelle Rieuf on December 23, 2016 at 4:30am — No Comments
This article was written on Database Friends. It is on Database, visualization and big data news. Blogs are about MySQL, PostgreSQL, Oracle, SQL Server and other DBMS.
MySQL is one of the most widely used open source relational database management systems in the world. With a total distribution amounting to more than 100 million worldwide, the software has become the first choice of large data management corporations spanning over a wide range of internet…Continue
Added by Emmanuelle Rieuf on December 16, 2016 at 8:30am — No Comments
This article was written by Sunil Ray. Sunil is a Business Analytics and Intelligence professional with deep experience.
Introduction – the difference in mindset
I started my career as a MIS professional and then made my way into Business Intelligence (BI) followed…Continue
Added by Emmanuelle Rieuf on December 15, 2016 at 10:00pm — No Comments
About the book
You’re convinced that you want to enter into a data science career. You’ve done your research and even started to learn some of the skills needed. But how do you go from an data science enthusiast to a data scientist at your dream company?
What does a data science interview look like? What do recruiters really think of your resume? Where are the data science jobs? Can you improve your odds of getting an interview by employing a few clever…Continue
Added by Emmanuelle Rieuf on December 7, 2016 at 3:00pm — No Comments