This post is the first in our series on machine learning (ML) algorithms. (See posts 2 and 3 on Logistic Regression and k-Nearest Neighbors.) In these posts, we explain the basic underlying concepts behind various algorithms, their pros and cons, and their most common applications. We are starting this discussion with the oldest ML algorithm, linear regression. It is an excellent starting point for learning about ML because many of the basic concepts involved are easy to explain in this context and because it is relatively easy to implement your very own linear regression algorithm. Continue reading Machine Learning Algorithm Series: Linear Regression
Editor’s Note: This post is the second part and conclusion from the Importance of Business Analysis in Data Science Projects series. Continue reading IMPORTANCE OF BUSINESS ANALYSIS IN DATA SCIENCE PROJECTS – PART II
One of the most publicized and arguably important use cases of Big Data technologies is their facilitation of Data Science techniques in solving complex business problems. Companies that embrace their data as a corporate asset can improve business processes and inform corporate strategies with insights gained through predictive and optimization analytic models. Although the business value of these projects is tremendous, their success is completely dependent on the ability to overcome an age-old enterprise challenge: bridging the communication and prioritization gaps between a company’s business units and IT department. While the IT department houses those most knowledgeable about the data and project-enabling technologies, project results are only relevant if they align with the needs of the business stakeholders. Continue reading Importance of Business Analysis in Data Science Projects – Part I
With obstacles like the Half Dome, Rope Cross, and Ninja Killer culminating in a slide down into a pool of muddy water, the charity run Goliathon posed a huge challenge to the team of Informationists who participated in the event on May 16 in Mullica Hill, New Jersey, as part of Knowledgent Cares. They had so much fun that their sights are already set on tackling the course again on October 3. Continue reading Knowledgent Informationists Get Dirty for Clean Water at Goliathon
Healthcare providers are facing an increasingly complex operational landscape. To remain competitive, they need to leverage the data at their disposal to improve patient outcomes, reduce readmissions, and provide high quality standards of care – all while controlling costs.
At Knowledgent, we’re helping our clients achieve this aim through groundbreaking projects that involve generating Unified Patient Records (UPRs) to facilitate analytics and promote a more individualized view of the patient. The creation of UPRs is necessary because good database design requires normalized data. In database parlance, this means that different kinds of information are stored in different tables so repetition is avoided and records cannot become contradictory. Continue reading Accelerating Patient-Centric Analytics with Unified Patient Records
In case you missed it, Knowledgent’s Data Scientist Dr. Mitchell Shuster recently served as a panelist on a round table webinar. Titled “The Business Potential of Machine Learning and Cognitive Computing,” the webinar featured expert insights on the next phase of machine learning, including deep learning, analytics, and cognitive computing.
“Machine learning and cognitive computing are becoming a critical portion of our technology infrastructure,” said Mitchell. “As with the rise of the Internet and social media, businesses that embrace these technologies will reap tremendous rewards and gain significant competitive advantage over those who fail to adapt to the changing landscape.”
Here are our major takeaways from the webinar: Continue reading “Beware the Hype!” And 4 Other Lessons in Machine Learning
What questions should I be asking to get the most out of my data with machine learning? What are best practices for using machine learning in my organization?
Our own Informationist and Data Scientist Mitchell Shuster will be tackling these questions and more on an IEEE-sponsored round table webinar tomorrow. Titled “The Business Potential of Machine Learning and Cognitive Computing,” this webinar will cover the next phase of machine learning, including deep learning, analytics and cognitive computing. Click here to register for the webinar.
Prior to the webinar, I sat down with Mitchell to talk about the hype and reality around machine learning: Continue reading Q&A: Mitchell Shuster on Machine Learning Hype vs. Reality
We are very excited to announce that our data scientist Mitchell Shuster will be a panelist on a round table webinar on machine learning! The webinar will take place on Wednesday, May 27, from 1-2 pm Eastern Time.
With summer fast approaching, many of our Informationists are taking the opportunity to curl up with a good book outdoors.
Coming from all walks of life, it’s no surprise that our Informationists have all different tastes in literature. Ranging from insightful profiles of major tech corporations to sci-fi novels that explore the human condition to deeply moving stories of love and courage, books help our Informationists kick back and relax, improve their minds, and learn new skills that they apply to improving lives and business through data.
Here’s a selection of some of the books our Informationists are reading: Continue reading What’s Good to Read This Summer? Our Informationists Weigh In.
We at Knowledgent know that it’s just as important to be able to balance our focus on helping improve lives and business through data with time to rest and recharge. With this new series, we’re putting a spotlight on the important best friends who are always there for us and help us relax after a hard day’s work: our pets.
Following our last post with Kariba Solution Partner Ray Diwakar and his seven-year-old German Shepherd Dog (GSD) Ruby, this week’s post features Data Scientist Mitchell Shuster and his cats Kahlan and Artemis!