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…Continue
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.
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…Continue
Added by Alex Marandon on April 19, 2016 at 11:40pm — No Comments
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…Continue
Added by Ashish kumar on April 19, 2016 at 1:30pm — No Comments
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.Continue
Added by Vincent Granville on April 19, 2016 at 9:44am — No Comments
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…Continue
Added by Vincent Granville on April 19, 2016 at 9:12am — No Comments
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…
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…Continue
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:
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…Continue
Added by Jennifer Livingston on April 18, 2016 at 9:00am — No Comments
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…Continue
Added by Emmanuelle Rieuf on April 18, 2016 at 7:30am — No Comments
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…Continue
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.
Added by Micah De Jesus on April 18, 2016 at 12:30am — No Comments
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 …Continue
Added by Emmanuelle Rieuf on April 16, 2016 at 1:00pm — No Comments
Added by NYC Data Science Academy on April 16, 2016 at 9:30am — No Comments
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…Continue
Added by BR Deshpande on April 16, 2016 at 9:00am — No Comments
What makes a good data analyst? This is a question I get regularly asked as I help people explore ways to see and understand their ever-growing volume of data. Analytical skills, communication skills, math, and attention to detail are usually thrown around as the essential skills required to be…Continue
Added by Kathleen VanDerAa on April 15, 2016 at 9:58am — No Comments
According to Wikipedia, deep learning (deep structured learning, hierarchical learning or deep machine learning) is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using multiple processing layers, with complex structures or otherwise, composed of multiple non-linear transformations.
Deep learning is sometimes defined as the intersection between machine learning and artificial intelligence. Many articles on deep…Continue
Added by Vincent Granville on April 15, 2016 at 8:49am — No Comments
An image is a concept. It is a mental picture that we have about things such as an object, a person, a group, an organization, or a nation. It is our notion or belief about something that is not physically present around us.
The image of any entity, be it a product or a person or a company, is its intangible asset. For example, the reliability (hence the high resale value) of a used car stems from its positive image as a dependable…Continue
Added by Nurur Rahman on April 15, 2016 at 8:30am — No Comments
The first trend is the internet of everything. Right now, we have electronics and sensors tracking the behavior of almost everything. And as a consequence of the increase in the number…Continue