A successful business requires new approaches to data management in this age. Modern advances in data science area provide an efficient solutions for numerous use cases.
Data science embraces a broad spectrum of tasks in the sphere of…Continue
Added by Igor Bobriakov on November 27, 2019 at 6:27am — No Comments
In my prior blog post, I wrote of a clever elf that could predict the outcome of a mathematically fair process roughly ninety percent of the time. Actually, it is ninety-three percent of the time and why it is ninety-three percent instead of ninety percent is also important.
The purpose of the prior blog post was to illustrate the weakness of using the minimum variance unbiased estimator (MVUE) in applied finance. Nonetheless, that begs a more general question of when and why it…Continue
Added by David Harris on November 26, 2019 at 1:44pm — No Comments
When ever we visit a client and present our proposal, we start wondering if it will be accepted or rejected by the customer. Usually, our customer will analyze our proposal, compare it with other competitors’ and make a decision.
In order to build our commercial forecast system, we need to assign a probability to every proposal we have presented and assign a numerical value to every one of them.
One way of doing this is multiplying the value of the proposal by the probability of…
Added by Pablo Gutierrez on November 26, 2019 at 3:05am — No Comments
Added by Sameer Nigam on November 25, 2019 at 11:30pm — No Comments
The standard error is really just a type of standard deviation. For this simple example, I've used three samples as an illustration of how the standard deviation and standard error differ as they relate to…Continue
Added by Stephanie Glen on November 25, 2019 at 1:21pm — No Comments
Summary: Too many solutions. We are at an inflection point where too many vendors are offering too many solutions for moving our AI/ML models to production. The very real risk is duplication of effort, fragmentation of our data science resources, and incurring unintended new technical debt as we bind ourselves to platforms that have hidden assumptions or limitations in how that approach problems.
Added by William Vorhies on November 25, 2019 at 9:44am — No Comments
(I will give you a hint. It’s in the name.)
This post is intended as a response to an interesting discussion on…Continue
Added by Lucas Finco on November 25, 2019 at 8:30am — No Comments
Clouds for doing quantum computing are becoming increasingly popular. Here is a list with links of those quantum clouds that already exist or are imminent. All are commercial but usually free for small jobs and open to the public. Most use open source q c software but some don't and have opted to keep their software proprietary. In Alphabetical Order. ✅…Continue
Added by Robert R. Tucci on November 25, 2019 at 7:30am — No Comments
Data Scientists help find insights about the market and help make products better. They are responsible for analyzing and handling a massive amount of structured and unstructured data and require various tools to do so. Some of the tools used by Data Scientists to carry out their data operations are mentioned below.
Designed for statistical operations, SAS is an open source proprietary software that is used to…
Added by Simran Agarwal on November 25, 2019 at 3:30am — No Comments
If there’s one thing that’s common to all businesses across all industries in the world, it’s that the customer is always the primary focus. While this holds for all sectors and companies as mentioned above, the fact remains that it can be somewhat more relevant to certain types of businesses. Take the manufacturing industry, for example. So, as more and more manufacturing companies seek to adopt an increasingly customer-focused path forward, they realize they need for modern solutions and…Continue
Added by Ryan Williamson on November 24, 2019 at 10:00pm — No Comments
I was formally (1998-2016) a Senior Research Fellow in the Institute of Educational Technology (IET) at the Open University (OU) in the UK. It was in that context that I first started thinking about the potential of Learning Analytics in my field which is Accessibility of eLearning and Disabled Student Support. Looking back through my work-related blog (…Continue
Added by Martyn Cooper on November 24, 2019 at 4:30pm — No Comments
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. To subscribe, follow this link. …
Added by Vincent Granville on November 24, 2019 at 2:30pm — No Comments
Digital transformation is getting some traction now.
There are many definitions of digital transformation.
For example, according to salesforce digital transformation is - Digital transformation is the process of using…Continue
Added by ajit jaokar on November 24, 2019 at 8:54am — No Comments
Originally posted by Igor Bobriakov.
Data science has become a widely used term and a buzzword as well. It is a broad field representing a combination of multiple disciplines. However, there are adjacent areas that deserve proper attention and should not be confused with data science. One of them is decision science. Its importance should not be underestimated, so it is useful to know the…Continue
Added by Vincent Granville on November 24, 2019 at 8:47am — No Comments
Originally posted by Deepak Kumar Gupta. A another interesting article on this topic can be found here.
Added by Vincent Granville on November 24, 2019 at 8:43am — No Comments
Originally posted by Deepak Kumar Gupta.
In the real world, many online shopping websites or service provider have single email-id where customers can send their query, concern etc. At the back-end service provider receive million of emails every week, how they can identify which email is belonged of a…Continue
Added by Vincent Granville on November 24, 2019 at 8:30am — No Comments
Data Science is the study of extracting meaningful insights from the data using various tools and technique for the growth of the business. Despite its inception at the time when computers came into the picture, the recent hype is a result of the huge amount of unstructured data that is getting generated and the unprecedented computational capacity that modern computers possess.
However, there is a lot of misconception among the masses about the true meaning of…Continue
Added by Divya Singh on November 23, 2019 at 8:30pm — No Comments
“If you buy a Tesla today, I believe you're buying an appreciating asset, not a depreciating asset.” – Elon Musk
Think about that statement for a second…you’re buying an appreciating asset, not a depreciating asset. And what is driving the appreciation of that asset? It’s likely courtesy of Tesla’s FSD (Full Self-Driving) Deep…Continue
Added by Bill Schmarzo on November 23, 2019 at 6:42pm — No Comments
Building the High Performing Team for Enterprise Data Analytics
Prashanth Southekal and Santhosh…Continue
Added by Prashanth Southekal, PhD on November 22, 2019 at 7:30am — No Comments
Do you want to extract csv files with Python and visualize them in R? How does preparing everything in R and make conclusions with Python sound? Both are possible if you know the right libraries and techniques. Here, we’ll walk through a use-case using both languages in one analysis.…
Added by Marija Zoldin on November 22, 2019 at 3:00am — No Comments