Nobody is an island. Even less so a data scientist. Assembling predictive analytics workflows benefits from help and reviews: on processes and algorithms by data science colleagues; on IT infrastructure to deploy, manage and monitor the AI-based solutions by IT professionals; on dashboards and reporting features to communicate the final results by data visualization experts; as well as on automatization features for workflow execution by system administrators. It really seems that a…Continue
Added by Rosaria Silipo on July 8, 2019 at 6:00am — No Comments
Artificial Intelligence and Machine Learning are accelerating and refining various industries. One of the most rapidly developing and progressive domains is Facial Recognition (FR). Its implementation in many spheres, from public security to retail and healthcare, only proves its potential.Continue
In my previous post, I discussed the relationship between role conflict and performance. I suggested that all things being equal, role conflict might be the primary determinant of employee performance. Companies direct all sorts of resources gathering data for recruitment purposes. All things being about the same, much of that data collection is irrelevant. …Continue
Added by Don Philip Faithful on July 7, 2019 at 6:11am — No Comments
Co-Integration in Time Series Analysis is when one data points is depended on other data points or follow the pattern. Example in capital markets Industry or sector leader company stock leads the direction and many small companies follows it. Example : Crude oil and Gasoline prices. Price of gasoline is dependent on Crude oil prices. Here Crude oil price always drives gasoline prices.
To analyze similar co-integration used Moody's corporate AAA and BBB Bond Yields. Corporate…Continue
Added by Kali Prasad on July 6, 2019 at 10:37pm — No Comments
I love watching the NBA’s Golden State Warriors play basketball. Their offensive “improvisation” is a thing of beauty in their constant ball movement in order to find the “best” shot. They are a well-oiled machine optimizing split-second decisions in an ever-changing landscape that is heavily influenced by questions such as:
Added by Bill Schmarzo on July 5, 2019 at 12:51pm — 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.
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
The energy sector is under constant development, and more of significant inventions and innovations are yet to come. The energy use has always been involved in other industries like agriculture, manufacturing, transportation, and many others. Thus these industries tend to enlarge…Continue
Exploratory Data Analysis or EDA is that stage of Data Handling where the Data is intensely studied and the myriad limits are explored. EDA literally helps to unfold the mystery behind such data which might not make sense at first glance. However, with detailed analysis, we can use the same data to provide miraculous results which can help boost large scale business decisions with excellent accuracy. This not only helps business conglomerations to evade likely pitfalls in the future but also…Continue
Added by Divya Singh on July 4, 2019 at 7:30pm — 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 Stacey Ronaghan.
This post attempts to consolidate information on tree algorithms and their implementations in…Continue
Added by Andrea Manero-Bastin on July 4, 2019 at 5:00am — 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
In addition to being the sexiest job of the twenty-first century, Data Science is new electricity as quoted by Andrew Ng. A lot of professionals from various disciplines and domain are looking to make a transition into the field of analytics and use Data Science to solve various problems across multiple channels. Being an inter-disciplinary study, one could easily mine data for various operations and help decision-makers make relevant conclusions to achieve…Continue
Added by Divya Singh on July 2, 2019 at 8:00pm — No Comments
Added by steve miller on July 2, 2019 at 9:00am — No Comments
Added by Shaily Baheti on July 2, 2019 at 12:30am — 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 architectures for the efficient acceleration of machine learning applications.
FPGAs are programmable chips that can be configured with tailored-made…Continue
Added by Chris Kachris on July 1, 2019 at 10:00pm — 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 8:30pm — No Comments