Added by Jesus Ramos on August 19, 2019 at 10:19am — No Comments
We are living in a time of slow yet steady insurgence of data science and AI in our lives. It spans more industries than we’d expect.
Over the past decade, Data Science has stretched out into almost every industry. Form industries like Automobiles and Healthcare to Finance as well as the Gaming Sector. It plays a significant part in the government sectors. So here are some instances of the most impactful…Continue
Added by Sudhanshu Ahuja on August 19, 2019 at 3:00am — No Comments
The amount of data generated today is astonishing. Research published by Seagate reports that by 2025, around 175 Zettabytes of data will be generated on an annual base. The colossal sets of collected, analyzed, monitored, and stored data is only…Continue
Added by Sandra Durcevic on August 16, 2019 at 12:30am — No Comments
Of late, a buzzword in marketing and analytics circles is CDP or Customer Data Platform. Chief Marketing Officers now have this new weapon in their arsenal to serve customers in an even better, faster and more granular manner.
A CDP is a “data unifying software”. Adding it on top of your martech stack helps manage your…
Added by Hemant Warudkar on August 13, 2019 at 2:12am — No Comments
Data Science is now becoming a highly famous and prestigious field and has also been termed as the "Sexiest job" of the 21st century said in the Harvard Business Review.
The number of data scientist jobs has grown manifolds in the past few years. According to data, the data science jobs crossed over 2 million and is continuing to increase rapidly in…Continue
Added by Rahul Dharia on August 12, 2019 at 9:02pm — No Comments
The term ‘data visualization’ was coined a couple of years ago. But storytelling finds its roots in the earliest of times. Using characters, events, event sequences, locations, time periods, emotions, numbers, etc., storytelling has always fascinated the humankind.
Today, data visualization narrates events, causes & consequences…Continue
Added by Bhushan Patil on August 6, 2019 at 5:00am — No Comments
Ever wondered how most of the fastest-growing jobs in the tech sector today were not even existing a few years ago. It is surveyed that the employees are worried about the skill gap, which is restricting them from shifting to companies which offer better skill development initiative.…Continue
Added by Dave Jarvis on July 31, 2019 at 8:56pm — No Comments
Building accurate models takes a great deal of time, resources, and technical ability. The biggest challenge? You almost never know what model or feature combination will end…
Added by Benjamin Waxer on July 25, 2019 at 4:12am — No Comments
Data is the new fuel- it drives businesses towards exponential growths. It has the power to transform operational and add intelligent insights with its immense potential. The key, however, lies with understanding data and its insights.
Logistics, like other domains, can also leverage from the several advantages of data. It all begins with what to do with the collected data. Data Science will come into the picture with its amalgamation of statistical &…Continue
Added by Bhushan Patil on July 21, 2019 at 8:37pm — No Comments
Excel is often poorly regarded as a platform for regression analysis. The regression add-in in its Analysis Toolpak has not changed since it was introduced in 1995, and it was a flawed design even back then. (See this link for a discussion.) That’s unfortunate, because an Excel file can be a very good place in which to build regression models, compare and refine them, create…Continue
Added by Robert Nau on July 21, 2019 at 7:00am — No Comments
Ecommerce sites generate tons of web server log data which can provide valuable insights through analysis. For example, if we know which users are more likely to buy a product, we can perform targeted marketing, improve relevant product placement on our site and lift conversion rates. However, raw web logs are often enormous and messy so preparing the data to train a predictive model is time consuming for data scientists.…
Added by Ayumi Owada on July 18, 2019 at 2:00pm — No Comments
ThinkData Works' co-founder and CEO Bryan Smith has been named Vice-Chair of the Government of Ontario’s first-ever Digital and Data Task Force. The task force is part of a wider provincial strategy to help Ontarians benefit directly from the data economy, improving the data literacy of both citizens and businesses while ensuring their personal privacy is protected.
The task force is being developed by the province’s Ministry of Government and Consumer Services, and is…Continue
Added by Lewis Wynne-Jones on July 16, 2019 at 5:30am — No Comments
Added by Lewis Wynne-Jones on July 16, 2019 at 5:00am — No Comments
If you are a recent graduate or someone preparing for your first data scientist position, then here are some tips to help you ace your interview!…Continue
Added by Ann Rajaram on July 11, 2019 at 2:52pm — No Comments
The use of Docker in conjunction with AWS can be highly effective when it comes to building a data pipeline.
Let me ask you if you have ever had this situation before. You are building a model in Python which you need to send over to a third-party, e.g. a client, colleague, etc. However, the person on the other end cannot run the code! Maybe they don't have the right libraries installed, or their system is not configured correctly.
Whatever the reason, Docker alleviates this…Continue
Added by Michael Grogan on July 5, 2019 at 8:30am — 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
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
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