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.
Featured Resources and Technical…Continue
Added by Vincent Granville on July 5, 2019 at 7:00am — No Comments
With every article, we keep proving that data science has found broad application in numerous business areas. Now, the turn came to the construction industry as well. The world is overloaded with data. It results in a steady improvement in…Continue
Added by Igor Bobriakov on July 5, 2019 at 5:00am — No Comments
Digitalization influences how businesses operate and build and maintain relationships with customers. With the internet open 24/7, consumers can save time and shop online at their convenience. In 2017, global eCommerce sales accounted for 10.2 percent of all retail sales ($2.3 trillion US). This figure is projected to reach 17.5 percent in 2021. Revenue from eCommerce sales is expected to grow to $4.88 trillion US.…Continue
Added by Kateryna Lytvynova on July 4, 2019 at 6:00am — No Comments
This article was written by James Loy.
Update: When I wrote this article a year ago, I did not expect it to be thispopular. Since then, this article has been viewed more than 450,000 times, with more than 30,000 claps. It has also made it to the front page of Google, and it is among the first few search results for…Continue
Added by Andrea Manero-Bastin on July 4, 2019 at 4:30am — No Comments
Machine learning models grow more powerful every week, but the earliest models and the most recent state-of-the-art models share the exact same dependency: data quality. The maxim “garbage in – garbage out” coined decades ago, continues to apply today. Recent examples of data verification shortcomings abound, including JP Morgan/Chase’s 2013 fiasco and this lovely…Continue
Added by Michał Frącek on July 4, 2019 at 4:21am — No Comments
My app Qubiter has a folder full of Jupyter notebooks (27 of them, in fact). Opening a notebook takes a short while, which is slightly annoying. I wanted to give Qubiter users the ability to peek inside all the notebooks at once, without having to open all of them. Qubiter’s new SUMMARY.ipynb notebook allows the user to do just that.
SUMMARY.ipynb scans the directory in which it lives to find all Jupyter notebooks (other than itself) in that directory. It then prints for every…Continue
Added by Robert R. Tucci on July 4, 2019 at 3:08am — No Comments
Here is our selection of featured articles and resources posted since Monday:
Added by Vincent Granville on July 3, 2019 at 7:30pm — No Comments
This Springer book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to…Continue
Added by Sergio Consoli on July 3, 2019 at 5:45am — No Comments
The housing market has undergone quite a change in the past decade, with more stringent lending criteria for housing having been enforced.
A key objective of financial institutions is to minimise the risk of mortgage lending by ensuring that the debtor is ultimately able to repay the loan.
In this example, multilevel modelling techniques are used to analyse data from the Federal Home Loan Bank…Continue
Added by Michael Grogan on July 3, 2019 at 3:01am — No Comments
Added by steve miller on July 2, 2019 at 9:00am — No Comments
Hotel cancellations can cause issues for many businesses in the industry. Not only is there the lost revenue as a result of the customer cancelling, but this can also cause difficulty in coordinating bookings and adjusting revenue management practices.
Data analytics can help to overcome this issue, in terms of identifying the customers who are most likely to cancel – allowing a hotel chain to adjust its marketing strategy accordingly.
To investigate how machine learning can…Continue
Added by Michael Grogan on July 2, 2019 at 3:00am — No Comments
Added by Shaily Baheti on July 2, 2019 at 12:30am — No Comments
Python is the most loved, dreaded, and wanted programming languages by most developers, according to StackOverflow survey. Popular among most professional software developers, Python was ranked the world’s seventh popular programming language.
A study by PYPL Popularity of Programming Language Index (a study that monitors the frequency of searches regarding the popular programming languages to learn) predicted that it showed that there was a growth of 17.1% during the last…Continue
Added by Yoey Thamas on July 2, 2019 at 12:29am — No Comments
Machine learning algorithms are extremely computationally intensive and time consuming when they must be trained on large amounts of data. Typical processors are not optimized for machine learning applications and therefore offer limited performance. Therefore, both academia an industry is focused on the development of specialized…Continue
Added by Chris Kachris on July 1, 2019 at 10:27pm — No Comments
A data scientist must know how to approach the extent of any problem; it means identifying features and figuring out the question that how to frame the desired answer is the key to become the most wanted data scientist. …Continue
Added by Nisha Dhiman on July 1, 2019 at 9:00pm — No Comments
Data science is a growing and promising discipline that has impacted various domains, including higher education. Owing to its ability to use precise methods and platforms to extract insights from data, several academic institutions are incorporating data science into their operations and educational curriculum. This helps them engage students, improve educational…
Added by Gaurav Belani on July 1, 2019 at 8:53pm — No Comments
Pooled, also referred to as “converged”, clusters in a unified data environment support disparate workload better than separate, siloed clusters. Vendors now provide direct support for converged clusters to run key HPC-AI-HPDA (AI, HPC, and High Performance Data Analytic) workloads.
The success of workload optimized compute servers has created the need for converged clusters as organizations have generally added workload optimized clusters piecemeal to support their disparate AI, HPC,…Continue
Added by Rob Farber on July 1, 2019 at 8:52am — No Comments
Summary: The annual Burtch Works salary survey tells us a lot about which industries are using the most data scientists and the difference between higher and lower skilled data scientists. Salary increases show us whether demand is increasing, and finally we take a shot at determining which skills are most in demand.
Added by William Vorhies on July 1, 2019 at 8:00am — No Comments
It has been suggested the role conflicts can lead to poorer performance in the workplace. Below I present the general dynamics: more role conflicts equate to less performance.
Performance can be expressed empirically - as in the case above using a formal scoring scheme. On the other hand, a qualitative approach can be used:…Continue
Added by Don Philip Faithful on July 1, 2019 at 6:50am — No Comments