Predictive analytics tools are a key asset in detecting natural disasters. With higher accuracy than other weather detection sensors, they can detect early signs of an oncoming calamity to prevent mistakes like the one that happened in 2016.…
Added by Ari Vivekanandarajah on July 12, 2021 at 5:30am —
How accurate is predictive analytics? Is it worth using for my business? How can forecasting and prediction help me in such an uncertain environment? These are all valid questions and they are they are questions your business (and your fellow business owners) must grapple with to understand the value of planning and analytical tools.
While predictive… Continue
Added by Kartik Patel on June 27, 2021 at 11:00pm —
Image Source: istockphoto
Wouldn’t it be nice to have a sneak-peek into the future of your business to make informed decisions and eliminate guesswork? With the help of predictive modeling, this is… Continue
Added by Michael Ethan on March 11, 2021 at 10:25pm —
Advanced Analytics helps to discover insights by applying machine learning to the analysis process. This enables improved decision-making and efficiency of the business. …
Added by Laura Jean on January 4, 2021 at 9:00pm —
Summary: This is a discussion of social injustice, real or perceived, promulgated or perpetuated by machine learning models. We propose a simple solution based on wide spread misunderstanding of what ML models can do.
This is a discussion of social injustice, real or perceived, promulgated or perpetuated by… Continue
Added by William Vorhies on September 11, 2020 at 1:38pm —
As a data scientist in an organization you frequently find yourself in a couple of situations:
- you have a dataset, you want to extract some useful information
- you have a business…
Added by Mab Alam on December 27, 2019 at 8:00pm —
Summary: A little history lesson about all the different names by which the field of data science has been called, and why, whatever you call it, it’s all the same thing.
A little reminiscence, or for those of you who are only recently data scientists, a little history lesson.
Our profession of… Continue
Added by William Vorhies on December 4, 2019 at 3:12pm —
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 —
Background: Civis began a data technology partnership with McDonald’s North America Marketing and Data Science teams in late 2017, and — after a year and a half of keeping our heads down — we jointly presented some of our key learnings recently at Advertising Week in New York.…
Added by Civis Analytics on March 6, 2019 at 8:00am —
Summary: True prescriptive analytics requires the use of real optimization techniques that very few applications actually use. Here’s a refresher on optimization with examples of where and how they’re best used.
Predictive analytics and optimization have gone hand in hand since the very beginning. But in… Continue
Added by William Vorhies on February 18, 2019 at 10:00am —
Wondering how the words, fashion, weather and predictive analytics are connected?
Here’s a poser – what is one of the biggest challenges before the global fashion industry today? Weather. You wouldn’t have guessed it, right?
Pick up any fashion magazine, read any fashion portal, white paper…. you name it, unpredictable weather is on the Top-5… Continue
Added by Hemant Warudkar on July 27, 2018 at 4:13am —
A smoothly running sensor data analytics tool may be just as difficult to manage as a symphony orchestra. Because every musician in an orchestra – and every part of an IoT system – needs to work properly and ‘harmonize’ with the others. But how do conductors make their orchestras work so nicely and sound so heavenly instead of creating a mismanaged cacophony? Obviously, there’s a lot of practice involved. But besides that, they definitely know what pitfalls they need to avoid. Which is why,… Continue
Added by imranali on July 7, 2018 at 4:30am —
R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises.
Learn the fundamentals of data analysis in the second edition of Data Analysis with R, authored by data scientist… Continue
Added by Packt Publishing on May 8, 2018 at 10:30pm —
Sales prediction is an important part of modern business intelligence. First approaches one can apply to predict sales time series are such conventional methods of forecasting as ARIMA and Holt-Winters. But there are several challenges while using these methods. They are: multilevel daily/weekly/monthly/yearly seasonality, many exogenous factors which impact sales, complex trends in different time periods. In such cases, it is not easy to apply conventional methods. Of course, there is… Continue
Added by Bohdan Pavlyshenko on March 8, 2018 at 9:00am —
Added by Peter Bruce on January 14, 2018 at 11:00am —
Finding out the difference between data scientists, data engineers, software engineers, and statisticians can be confusing and complicated. While all of them are linked to data in a way, there is an underlying difference between the work they do and manage.
The growth of data and its usage across… Continue
Added by Ronald van Loon on December 19, 2017 at 1:00am —
Summary: Which is more important, the data or the algorithms? This chicken and egg question led me to realize that it’s the data, and specifically the way we store and process the data that has dominated data science over the last 10 years. And it all leads back to Hadoop.
Recently I was challenged to speak on the role of data in data… Continue
Added by William Vorhies on November 28, 2017 at 10:36am —
One of the main goals in the Bitcoin analytics is price forecasting. There are many factors which influence the price dynamics. The most important factors are: the interaction between supply and demand, attractiveness for investors, financial and macroeconomics indicators, technical indicators such as difficulty, how many blocks were created recently, etc. A very important impact on the cryptocurrency price has trends…
Added by Bohdan Pavlyshenko on October 26, 2017 at 11:30pm —
Today, data scientists are generally divided among two languages — some prefer R, some prefer Python. I will not try to explain in this article which one is… Continue
Added by Marija Zoldin on September 26, 2017 at 10:00am —
Here is our list of featured articles and resources posted since Monday.
Added by Vincent Granville on September 21, 2017 at 8:30am —