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Never Wait for a Job to Start Working in Data Science
You finally finished that college CS degree, completed hundreds of hours of training online, got your certifications, or simply have the skills you need to transition. The bottom line is, you are ready to start working in data science, an incredibly exciting field. And then, you... Read more
Promoting the Responsible Use of AI in Health Care
Artificial intelligence (AI) holds tremendous promise as a means of improving the efficiency and quality of health care delivery— from enhancing patient outreach and engagement, to managing medical and pharmacy inventory, to identifying patients at the greatest risk of disease progression. The tangible benefits of AI... Read more
Fast, Visual, and Explainable ML Modeling With PerceptiLabs
Pure-code ML frameworks like TensorFlow, have become popular for building ML models because they effectively offer a high-level grammar for describing model topologies and algorithms. This is a powerful approach, but it has limitations for providing insight and explainability of models. These issues are further magnified... Read more
Making Explainability Work in Practice
Complex ‘black box’ models are becoming more and more prevalent in industries involving high-stakes decisions (such as finance, healthcare, insurance). As machine learning algorithms take a prominent role in our daily lives, explaining their decision will only grow in importance via explainability. By now there is... Read more
The Importance of Industry 4.0 and AI Adoption in a Changing Industry
I don’t need to tell you how much the world has changed over the last year – a (hopefully) once-in-a-lifetime pandemic took over our lives and caused massive disruption around the world. The way we live, work, and interact with each other was completely flipped on... Read more
Why Causal Machine Learning is the Next Revolution in AI
Editor’s note: Robert Ness is a speaker for ODSC East 2021. Check out his talk, “Causal Machine Learning Blitz,” there! Causal modeling and inference are perhaps at the core of the most interesting questions in data science. A common task for a data scientist at a... Read more
Black Box Optimization Using Latent Action Monte Carlo Tree Search (LaMCTS)
Black box optimization has numerous applications in industries. From a/b testing to experimental designs of new ads or UI, hyper-parameter tuning in the machine learning models, or to find the optimal configuration of a system, black-box optimization tries to optimize your decision solely by exploring the... Read more
Build NLP and Conversational AI Apps with Transformers and Large Scale Pre-Trained Language Models
Transformers have taken the AI research and product community by storm. We have seen them advancing multiple fields in AI such as natural language processing (NLP), computer vision, and robotics. In this blog, I will share some background in conversational AI, NLP, and transformers-based large-scale language... Read more
Preparations for a Post-Pandemic Retail Environment
Covid-19 has challenged us to redesign multiple aspects of our life and this has inevitably led to wide-ranging impact across business in multiple different sectors. The retail industry has especially been disrupted as people seek convenience from the safety and comforts of their homes. As the... Read more
Brand Voice: Deep Learning for Speech Synthesis
The production of artificial natural-sounding human speech is a fascinating topic due to its complexity and surprising results, with applications that range from chatbots to the automatization of audio content in news media. One obvious example of a Text-to-Speech (TTS) application for news media is a... Read more