Added by Daria Baidakova on September 29, 2021 at 2:00am — No Comments
In the media and communication industry, writers are frequently confronted with huge volumes of textual material. They are having significant difficulty extracting structured knowledge from these papers, and the text is being underutilized, perhaps leaving critical information unknown.…Continue
Added by Rayan Potter on September 2, 2021 at 9:11pm — No Comments
Deep learning has wide application in artificial intelligence and computer vision backed programs. Across the world, machine learning has added more value to a range of tasks using key methodologies of artificial intelligence such as natural language processing, artificial neural networks and…Continue
Added by Rayan Potter on September 2, 2021 at 9:09pm — No Comments
Added by Olha Zhydik on August 26, 2021 at 3:00am — No Comments
It’s not a secret that web scraping can be complex and challenging. Part of that challenge is the fact that much of the process consists of repetitive and…
Added by Julius Cerniauskas on January 21, 2021 at 4:00am — No Comments
Trustable data is defined as data that comes from reliable sources and used according to its intended and delivered in the appropriate formats and time frames for the specific users.
Trustable data helps in effective decision making. The properties mentioned in the definition makes data trustworthy for effective decision making.
Trust Factors of data:
Trustable data are good only if they meet certain basic requirements. Here are some of the…Continue
Added by DQLabs AI on December 22, 2020 at 11:30pm — No Comments
Summary: Things are getting repetitious and that can be boring. Still, looking at lessons from the 90s it’s clear there are at least one or two decades of important economic advances that will based on our current AI/ML. Then some thoughts on where that next really huge breakthrough will come from that will return our initial excitement.
Added by William Vorhies on December 8, 2020 at 11:12am — No Comments
Summary: There is now sufficient experience among mid and large sized companies starting their AI journey to identify a single best practice for moving from AI experimentation to scale-up: the AI COE (Center of Excellence).
If you are a mid-sized business, government organization, or educational…Continue
Added by William Vorhies on December 2, 2020 at 3:18pm — No Comments
Summary: Let’s start by clarifying the difference between RPA (Robotic Process Automation) and IA (Intelligent Automation). Then we’ll show why AI/ML inside Intelligent Automation is the secret sauce that really makes this work.
Added by William Vorhies on November 18, 2020 at 9:00am — No Comments
With the digital world growing competitive by the day, everyone is trying to understand their customers better and make finance, product development, and marketing decisions based on real data for a better return on investment (ROI). If you don’t make use of data, there is a chance you will lag behind or, at least, use more money and energy to keep up with your data-driven competitors. That said, data needs to be accurate and of high quality to be useful. Bad data is inaccurate, unreliable,…Continue
Added by DQLabs AI on November 10, 2020 at 9:44pm — No Comments
Summary: Some industries are a clear slam-dunk for AI/ML applications and some less so. The legal, regulatory, and compliance businesses (law firms, internal legal departments, and the contract review and regulatory compliance departments of heavily regulated industries) fall in this last category. This is a review of seven companies found by TopBots to be successful; pointing to opportunities others can follow.
Added by William Vorhies on November 4, 2020 at 10:00am — No Comments
Added by William Vorhies on October 24, 2020 at 11:30am — No Comments
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.
Added by William Vorhies on September 11, 2020 at 1:38pm — No Comments
Summary: The annual Burtch Works salary survey with data through April shows that opportunities and salaries are still excellent for both new and experienced data scientists. They also offer some anecdotal observations about the impact of the first few months of COVID on our work and opportunities.Continue
Added by William Vorhies on September 1, 2020 at 8:00am — No Comments
Enterprise software, as well as other kinds, remains a complicated endeavor, thus necessitating the use of modern means to gauge, analyze, and adapt their performance. And one of the most popular technologies in the performance engineering market right now is machine learning. Since it has demonstrated an unparalleled ability to not only help foresee performance issues and fix them. When used in the right manner — this combination can also help performance engineering teams to steer clear of…Continue
Summary: Transfer Learning (TL) may be the most important aid to adoption of deep learning in the last several years. This new LEEP measure predicts the accuracy of the transfer and should make TL faster, cheaper, and better.
Added by William Vorhies on August 21, 2020 at 10:26am — No Comments
Summary: Less than 9%? What this study really shows and what we should take away from it.
Wow. Less than 9%! Can this be true? Well according to a large scale survey study conducted by the US Census Bureau it’s actually a…Continue
Added by William Vorhies on August 3, 2020 at 1:00pm — No Comments
In the era of the Internet, the ability to crunch large amounts of data and process it with speed and efficiency has become essential for businesses to survive. But you try sitting down and going through all that data by hand: you'll get done sometime in the year 2050 if you're lucky.
That's where machine learning comes to the rescue. But…Continue
Summary: Bias in modeling has long been a public concern that is now amplified and focused on the disparate treatment models may cause for African Americans. Defining and correcting the bias presents difficult issues for data scientists that need to be carefully thought through before reaching conclusions.
Added by William Vorhies on June 29, 2020 at 11:31am — No Comments
Summary: Explaining data science to a non-data scientist isn’t as easy as it sounds. You may know a lot about math, tools, techniques, data, and computer architecture but the question is how do you explain this briefly without getting buried in the detail. You might try this approach.