Rumman Chowdhury’s job used to involve a lot of translation. As the “responsible AI” lead at the consulting firm Accenture, she would work with clients struggling to understand their AI models. How did they know if the models were doing what they were supposed to? The confusion often came about partly because the company’s data scientists, lawyers, and executives seemed to be … [Read more...] about Worried About Your Firm’s AI Ethics? These Startups Are Here to Help. « Machine Learning Times
Machine Learning
Data in, Predictions out
It is always advantageous for data scientists to follow a well-defined data science workflow when working with big data. Regardless of whether a data scientist wants to perform analysis with the motive of conveying a story through data visualization or wants to build a data model — the data science workflow process matters. A standard workflow for data science projects ensures … [Read more...] about Data in, Predictions out
How to Navigate the Increasingly Symbiotic Dynamic Between Executives and Universities « Machine Learning Times
Book Review of Closing the Analytics Talent Gap: An Executive’s Guide to Working with Universitiesby Dr. Jennifer Priestley and Dr. Robert McGrath (CRC Press 2021, part of the Data Analytics Applications series, edited by Jay Liebowitz). We started Enolytics a few years ago in order to fill the gap we saw between the abundance of data that was increasingly available within the … [Read more...] about How to Navigate the Increasingly Symbiotic Dynamic Between Executives and Universities « Machine Learning Times
Rethinking Threat Intelligence with the LEAD Framework
There are commonly two types of threat intelligence programs: Early Stage programs focus primarily on Indicators of Compromise (IoC), which are the traditional tactical — and often times reactive — indicators used in threat detection. In contrast, Mature Stage programs focus on behavioral indicators or Indicators of Attack (IoA), which is a more proactive way of determining the … [Read more...] about Rethinking Threat Intelligence with the LEAD Framework
Gradient Descent Models Are Kernel Machines (Deep Learning) « Machine Learning Times
Originally published in infoproc.blogspot.com, Feb 7, 2021. This paper shows that models which result from gradient descent training (e.g., deep neural nets) can be expressed as a weighted sum of similarity functions (kernels) which measure the similarity of a given instance to the examples used in training. The kernels are defined by the inner product of model gradients in the … [Read more...] about Gradient Descent Models Are Kernel Machines (Deep Learning) « Machine Learning Times
Area Monitoring — Expert Judgement Application
This is a multi-part series about machine learning and EO data supporting Common Agriculture Policy. Find information about related blog posts at the bottom.In Area Monitoring (AM) having “better than 90% accuracy” ML results could still mean that 10% of the farmers might be wrongly penalized or that the Member State has to return the funds distributed inappropriately. Both … [Read more...] about Area Monitoring — Expert Judgement Application
How Can We Fix the Data Science Talent Shortage? « Machine Learning Times
Originally published in Springboard Blog, Jan 22, 2021. Data science might just be the most buzzed-about job in tech right now, but its pop culture sheen conceals some of the harsh realities of being a fresh graduate in the industry. The job topped LinkedIn’s yearly Emerging Jobs Report from 2016 to 2019 consecutively (it is now at #3). But when Springboard data science alum … [Read more...] about How Can We Fix the Data Science Talent Shortage? « Machine Learning Times
AI/ML music series 2: Imitation Game by Artemi-MariaGioti
The piece “Imitation game” (2018) is written by Artemi-Maria Gioti. It is an interactive composition for human and robotic percussionist, incorporating machine learning and musical robotics. The composition is based on a dynamic form, shaped by decisions made by the musician and the robotic percussionist in real-time. The robotic percussionist interacts with the human based on … [Read more...] about AI/ML music series 2: Imitation Game by Artemi-MariaGioti
How to Apply Machine Learning to Business Problems « Machine Learning Times
By: Daniel Faggella, Emerj Originally published in Emerj, April 25, 2020. It’s easy to see the massive rise in popularity for venture investment, conferences, and business-related queries for “machine learning” since 2012 – but most technology executives often have trouble identifying where their business might actually apply machine learning (ML) to business problems. With new … [Read more...] about How to Apply Machine Learning to Business Problems « Machine Learning Times
Gradio vs Streamlit vs Dash vs Flask
Machine learning models are exciting and powerful, but they aren’t very useful by themselves. Once a model is complete, it likely has to be deployed before it can deliver any sort of value. As well, being able to deploy a preliminary model or a prototype to get feedback from other stakeholders is extremely useful.Recently, there has been an emergence of several tools that Data … [Read more...] about Gradio vs Streamlit vs Dash vs Flask