Myth #1: You can only do research in an academic setting. Not true. There are plenty of research labs owned by big and small companies and organizations, including government, as well as abroad. In my case, I own and manage my self-funded research lab, publishing in my own niche media outlets (see …Continue
The Zipf distribution is used to model situations in which a few observations have a very high value (or impact) and account for a large part of the total, while a very long tail of observations have medium, small, or very small values. A bit like …Continue
Added by Vincent Granville on March 7, 2018 at 7:30pm — No Comments
Here, I've used the famous Iris Flower dataset to show the clustering in Power BI using R. I've used the K-means clustering method to show the different species of Iris flower.
About the dataset: The Iris dataset has 5 attributes (Sepal length, Sepal width, Petal width, Petal length, Species). The 3 different species are named as Setosa,…Continue
Background: Business intelligence software casts a wide net. Software for site selection, customer segmentation, marketing tests, employee productivity, operational metrics, sentiment analysis, profitability sectors and mapping tools all fall in this category.
Businesses are constantly challenged with business intelligence software questions such as:
· Should we “Build or Buy”?
· Should we “Retain, Upgrade, or Replace”…Continue
Added by Howard Friedman on March 7, 2018 at 5:00am — No Comments
It seems like it has been a long time since big data was all the hype in tech. Over the past year, it’s blockchain that has been grabbing headline after headline. It does appear fitting since blockchain is proving to be quite the disruptive force. This, however, doesn’t mean that data stakeholders can just tune out all this blockchain frenzy. Data is still the lifeblood of modern tech. Disruptive technologies and data will inevitably have an interplay.…Continue
Added by Peter on March 6, 2018 at 8:30pm — No Comments
This article was written by John Hammink. John is Chief Evangelist for Treasure Data. An 18-year veteran of the technology and startup scene, he enjoys travel to unusual places, as well as creating digital art and world music.
With the explosion of “Big Data” over the last few years, the need for people who know how to build and manage data-pipelines has grown. Unfortunately, supply has not kept up with demand and there seems to be a shortage of engineers focused on…Continue
Added by Emmanuelle Rieuf on March 6, 2018 at 6:00pm — No Comments
Tuesday of Strata Data Conference is my favorite of the four days. The calm before the storm of the keynotes and short presentations of Wednesday-Thursday, Tuesday revolves on half day training sessions that afford reasonably deep dives into technical data science topics. This year my choices were Using R and Python for scalable data science, machine…Continue
Added by steve miller on March 6, 2018 at 3:00pm — No Comments
Summary: A major problem with chatbots is that they can only provide information from what’s in their knowledge base. Here’s a new approach that makes your chatbot smarter with every question it can’t answer, making it a self-learning lifelong learner.
If you’ve been keeping up with the…Continue
The problem this blockchain project is trying to solve is allowing a number of people to create a knowledge product in a decentralized way, without a person dictating who should contribute and who should not. Whose contribution to the knowledge product will be accepted or rejected is done by a consensus of all participating members. The system should allow transparently assessing and scoring the contribution of each of the participant to the final product. The system should also allow…Continue
Added by Issoufou Seidou Sanda on March 5, 2018 at 3:30am — No Comments
We went from analog to digital few decades back and then GPRS, Edge & came 3G, which brought data and web…Continue
Added by Sandeep Raut on March 4, 2018 at 6:30pm — No Comments
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation, outliers, regression, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, time series, cross-validation, model fitting, dataviz,…Continue
Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week.
Added by Vincent Granville on March 4, 2018 at 8:00am — No Comments
As everyone knows Machine learning studies computer algorithms for learning to do stuff. We might, for instance, be interested in learning to complete a task, or to make accurate predictions, or to behave intelligently. The learning that is being done is always based on some sort of observations or data, such as examples…direct experience, or instruction. So in general, machine learning is about learning to do better in the future based on…Continue
Added by Jayesh Bapu Ahire on March 3, 2018 at 6:00am — No Comments
They come in various shapes: infographics, cheat sheets, periodic tables, one-picture articles, and even maps. They cover everything: IoT, AI, machine learning, data science, deep learning, Hadoop, Python, R, dataviz, statistical theory, big data - you name it. Below is a selection that is most relevant to our readers.
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees,…Continue
Knowledge is power
With IDC estimating that the data mountain has now reached five zettabytes, it is not a case of a business not having enough data to make business decisions, but arguably knowing too much. For many, it is the old adage of not being able to see the wood from the trees. Armed with all this information, businesses should be able to operate more efficiently and accurately than ever before, but many simply don’t have the key to unlock valuable…Continue
Added by Mathias Golombek on March 2, 2018 at 5:30am — No Comments
"No one wants to be sold but everyone wants to buy."
Most of us hate being sold. The moment we know someone is selling something, we keep our guards up.
In the book, The Challenger Sale, authors Mathew Dixon and Brent Adamson surveyed over 6000 salespeople from around the world and found that ‘challenger salespeople’ outperformed every other group. Who are these challenger salespeople? These…Continue
Added by Rudradeb Mitra on March 1, 2018 at 9:00pm — No Comments
Ask for feedback from just about any critic of the R statistical package and you'll hear two consistent responses: 1) R is a difficult language to learn, and 2) R's data size limitation to physical RAM consigns it to toy academic applications. Having worked with R for over 15 years, I probably shared those views to some extent early on, but no longer.
Yes, R's a language where array-oriented processing and functional…Continue
Added by steve miller on March 1, 2018 at 9:00am — No Comments
Narrowband IoT (NB-IOT) is a Low Power Wide Area Network (LPWAN) radio technology standard developed to permit a various services and devices to be connected using telecommunications bands. Narrowband Internet of things is a narrowband radio technology designed…Continue
Added by Alisha Wilson on March 1, 2018 at 2:00am — No Comments
The manufacturing industry has always has been open to adopting latest technologies. Industrial robots and drones have been a part of the manufacturing industry subsequently since 1960s. The next automation revolution is just around the turn and the US Manufacturing Sector is awaiting this technological advancements eagerly. The adoption of AI by the companies can keep…Continue
Added by Alisha Wilson on March 1, 2018 at 1:30am — No Comments