In a meeting with engineering leadership, I was told, "We'll tack on the AI later."
While doing ethnographic testing with a β customer, I was asked if the AI would just learn and then do everything perfectly.
Since its advent in 1991, Python has been the choice of coders due to its simple features that include ease of understanding and readability of code but not limited to just that. There have been lots of changes in the codebase over time due to the contribution from developers worldwide. Simple syntax and faster execution make Python a favorable language among programmers. It is used widely to create websites and primarily in big data operations. To make the task of running…Continue
Added by Digital Defynd on January 24, 2020 at 2:30am — No Comments
There is no doubt that Google is an absolute giant in the IT world. It creates various software tools for almost any imaginable area of activity existing today. Whatever you could want, Google, probably, has a solution. Either it is a smart voice helper or an…Continue
Added by Igor Bobriakov on January 23, 2020 at 11:30pm — No Comments
Added by Siddhaling Urolagin on January 23, 2020 at 9:30pm — No Comments
Sometimes it just takes a simple, provocative statement to kick-off the innovation process – to remove an everyday given like driving a car or possessing a landline phone or centralizing all of your data in the cloud – to fuel the innovation process. Henrik Christensen, director of University San Diego's Contractual Robotics Institute, issued such a provocative statement:
“My own prediction is that kids born today will never get to drive a car.”
I have recently been…Continue
Added by Bill Schmarzo on January 23, 2020 at 1:30pm — No Comments
Added by Mark Cramer on January 23, 2020 at 12:30pm — No Comments
Abhijeet, the HR head has deployed artificial intelligence in his organization with the objective of taking care of his employees and to stay ahead of the competition. He has a vision in improving overall efficiency of the organization that leads to employee productive growth. He also wants the AI to help him get minute details of HR processes that…Continue
Added by Sukumar Jena on January 23, 2020 at 12:00pm — No Comments
Here is our selection of featured articles and technical resources posted since Monday:
Added by Vincent Granville on January 22, 2020 at 9:30pm — No Comments
The role of data is changing significantly with advanced methodologies used for upgrading sales and integrating business intelligence in the organisational schema for better outcomes. But in the absence of proper tools and techniques to manage and organise such a large pool of data, results might appear too far-fetched. So, what is the way out to handle bundles of unstructured data and harness its true potential for catalysing the growth? Data warehousing is the solution that…Continue
Added by PS Dhillon on January 21, 2020 at 10:30pm — No Comments
Added by Sandeepkumar on January 21, 2020 at 1:00pm — No Comments
It is sometimes said that you don't need to know math to be a data scientist. Sometimes the opposite is said, after all, data science is supposed to be a science! Regardless, below are a few of my articles featuring how data science and math can benefit from each other - not just math to solve data science problems, but also data science to solve math problems.
Kubernetes is a technology that allows us to isolate an application. That is good but how can we scale this? Of course, we should create new containers.
But, how many containers should we have at the same time? How many…Continue
Added by Igor Bobriakov on January 21, 2020 at 7:30am — No Comments
Models are simplification or approximation of reality and hence they will not capture all of reality. “All models are wrong, but some are useful” is a famous quote by George Edward Pelham Box (1919–2013). George Box was a British mathematician and professor of statistics at the University of Wisconsin. Statisticians develop theoretical models to predict the behaviour of certain process. The meaning of this quote is that every single model will be wrong and it never represents the exact…Continue
In the previous post, ten strategies to implement ai on the cloud and edge, I discussed strategies for end to end deployment for machine learning modules.
How this relates to Agile?
Deployment of AI comes within the scope the normal SDLC (software development lifecycle)
So, normal Agile techniques like scrum, sprints, backlog…Continue
Added by ajit jaokar on January 20, 2020 at 1:06pm — No Comments
Summary: Just how much should you trust your AI systems? Best practice points to constant review, strong governance, and the willingness to override results that seem illogical.
Added by William Vorhies on January 20, 2020 at 8:26am — No Comments
Choose your format to work on the same analytical process among graphical composer (IRIS BPL), notebook (Jupyter) or IDE (IRIS Studio/Atelier):
This platform-centric approach to developing analytical tools and solutions aiming to maximize the advantages of combining multiple analytic toolsets (AI/ML, BI, SQL, Quantum, IoT, MapReduce, NLP,…Continue
Added by Sergey Lukyanchikov on January 19, 2020 at 9:30pm — 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. …Continue
Added by Vincent Granville on January 19, 2020 at 4:30pm — No Comments
Out of all the machine learning algorithms I have come across, KNN has easily been the simplest to pick up. Despite it’s simplicity, it has proven to be incredibly effective at certain tasks (as you will see in this article).
And even better? It can be used for both classification and regression problems!…Continue
Added by TcGyver on January 19, 2020 at 9:00am — No Comments
Having spent the better part of the last decade helping organisations in the U.S. and the U.K. use data to drive profit, efficiency, and performance improvements, I thought it would be helpful to jot down best practices for organizations that are looking to get the most value out of their enterprise-level financial and operational data sets.
Every organisation entering the roaring 20s knows that they must use their data as a strategic differentiator to gain a competitive advantage and…Continue
Added by Fahad Zaidi on January 19, 2020 at 6:00am — No Comments
How to build a project from scratch by using a latest, state-of-the-art AI technology stack?
After spending a few years working on data science - enriched products, we tried more than 10 different workflow concepts - adopted scrum & agile, waterfall, iterative kanban canvas etc.
As a result, we've drafted our own data science project development workflow that allows us to iterate over data science hypotheses, process and acquire data, build…Continue
Added by Max Frolov on January 19, 2020 at 3:00am — No Comments
In my previous post, I discussed the differences between Business Intelligence and Business Analytics. Two other terms that are often confused are Business Analytics and Data Analytics, but they are actually quite separate entities. This one picture highlights the differences between the two…Continue
Added by Stephanie Glen on January 18, 2020 at 7:12am — No Comments