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
Added by Ryan Williamson on August 30, 2020 at 11:00pm — No Comments
AI for People and Business is an AI book and AI strategy framework. Here's the official book trailer where I explain important topics that are covered in the book, as well as the beneficial aspects of reading it and the importance of developing a strong AI strategy.
FREE CHAPTER DOWNLOAD -…Continue
Added by Alex Castrounis on August 27, 2020 at 7:20am — No Comments
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
Added by Or Hillel on July 22, 2020 at 9:59pm — No Comments
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.
Summary: What is an AI Product Manager and how do you know when you need one.
The role of Product Manager (PM) can mean many things dependent on the specifics of the company, its markets, its channels, and the variety of its products. It’s almost impossible to put a single label on the responsibilities of a…Continue
Summary: In a comprehensive study of 18 recently presented DNN advancements in top-N recommenders, only 7 presented sufficient data to allow reproduction. Worse, of the 7 that could be reproduced none showed an actual improvement over simple linear and KNN techniques when those were properly optimized.
Added by William Vorhies on May 19, 2020 at 12:53pm — No Comments
Summary: As we have become ever more enamored with DNNs, and their accuracy and utility has been paced only by their complexity we will need to answer the question of whether we will ever really be able to explain what goes on inside.
Added by William Vorhies on May 11, 2020 at 2:41pm — No Comments
The world has been witness to some profound changes over the past couple of decades. For example, we can shop for furniture without needing to leave our house or even send money halfway across the world with a few taps on your smartphone’s screen. However, there is one aspect of human existence that has undergone some of the most profound changes of them all — learning. Yep. Today, education is no more confined to schools, colleges, or other educational facilities. Today, students have not…Continue
Added by Ryan Williamson on May 6, 2020 at 8:52pm — No Comments
Summary: Analytic Platforms are rapidly being augmented with features previously reserved for data scientists. They are presented as easy to use but require substantial data literacy and advanced DS skills for the most complex. Business users and analysts can pursue more complex problems on their own, but need good oversight.
Added by William Vorhies on May 4, 2020 at 1:06pm — No Comments
Summary: Now that you have a little time for introspection, how about reviewing the performance of your chatbots.
Added by William Vorhies on April 28, 2020 at 11:12am — No Comments
Let’s start with some simple real-lie examples that we’re sure you all must have experienced.
You watch Netflix and it offers you viewing suggestions.
Twitter shows you relevant tweets on your timelines instead of recent ones.
Quora offers specific answers to all types of questions you…Continue
Added by Tanya Kumari on April 23, 2020 at 10:27pm — No Comments
Summary: COVID-19 and the changes it creates in the business environment for the next 12 to 24 months means our current AI strategies need to thoroughly reviewed and probably retargeted.
Added by William Vorhies on April 21, 2020 at 10:53am — No Comments
Summary: High stakes models like those that allocate scarce resources to competing hospitals are headline news. New thinking contrasting model-based versus model-free learning are emerging to describe new conditions we must consider before building or evaluating those models.
Added by William Vorhies on April 13, 2020 at 2:01pm — No Comments
Summary: Whether trying to predict the life outcomes of disadvantaged kids or to model where ventilators will be most needed, a little humility is in order. As this study shows, the best data and the broadest teams failed at critical predictions. Getting the model wrong, or more importantly using it in the wrong way can hurt all of us.
Added by William Vorhies on April 6, 2020 at 2:56pm — No Comments
Summary: An interesting documentary about the earliest days of AI/ML and my alternate take on how we should really be describing the development of our profession to the newly initiated.