Are you a researcher or data scientist / analyst / ninja? Do you want to learn Bayesian inference, stay up to date or simply want to understand what Bayesian inference is? Then this podcast is for you! You'll hear from researchers and practitioners of all fields about how they use Bayesian statistics, and how in turn YOU can apply these methods in your modeling workflow. When I started learning Bayesian methods, I really wished there were a podcast out there that could introduce me to the methods, the projects and the people who make all that possible. So I created 'Learning Bayesian Statistics', where you'll get to hear how Bayesian statistics are used to detect black matter in outer space, forecast elections or understand how diseases spread and can ultimately be stopped. But this show is not only about successes -- it's also about failures, because that's how we learn best. So you'll often hear the guests talking about what *didn't* work in their projects, why, and how they overcame these challenges. Because, in the end, we're all lifelong learners! My name is Alex Andorra by the way, and I live in Estonia. By day, I'm a data scientist and modeler at the https://www.pymc-labs.io/ (PyMC Labs) consultancy. By night, I don't (yet) fight crime, but I'm an open-source enthusiast and core contributor to the python packages https://docs.pymc.io/ (PyMC) and https://arviz-devs.github.io/arviz/ (ArviZ). I also love https://www.pollsposition.com/ (election forecasting) and, most importantly, Nutella. But I don't like talking about it I prefer eating it. So, whether you want to learn Bayesian statistics or hear about the latest libraries, books and applications, this podcast is for you -- just subscribe! You can also support the show and https://www.patreon.com/learnbayesstats (unlock exclusive Bayesian swag on Patreon)! more

The forecasting, demand planning and S&OP podcast designed for practitioners in the field. Brought to you by the Institute of Business Forecasting with your host Eric Wilson, ACPF. more

Forecasting Impact is a bimonthly podcast that aims to disseminate the science and practice of forecasting by introducing prominent academics, practitioners, and visionaries in the forecasting domain. Our vision is to help grow the forecasting community, foster collaboration between academia, industry, and governments, and promote scientific forecasting and good practices. We will discuss a range of forecasting topics in economics, supply chain, energy, social goods, AI, machine learning, data analytics, education, healthcare, and more. Forecasting Impact episodes are also available on the IIF YouTube Channel @IIForecasters . Podcast Team Chair and Co-host: Dr. Laila Ahadi-Akhlaghi, Senior Technical Advisor at JSI. Additional co-hosts: Dr. Mahdi Abolghasemi, Lecturer in Data Science at The University of Queensland, George Boretos, Founder & CEO at FutureUP, Dr. Faranak Golestaneh, Data Science Senior Manager at Commonwealth Bank of Australia, Mariana Menchero, Senior Forecaster at Nixtla, and Arian Sultan Khan, Data Analyst at VAN Co-hosts in the past have included: Michał Chojnowski, Shari De Baets, Elaine Deschamps, Dr. Sevvandi Kandanaarachchi, Bahman Rostami-Tabar, Anna Sroginis, and Sarah Van der Auweraer. We welcome your feedback, questions, and suggestions. Please contact us at forecastingimpact@forecasters.org more

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast. As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact. Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy. We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science. more

Eric Siegel covers why machine learning is the most important, most potent, and most misunderstood technology. And did I mention most important?Yup, it's the most important yet most new ML projects fail to deliver value. This podcast will help you:- Make sure machine learning is effective and valuable- Catch common machine learning oversights- Understand ethical pitfalls concretely- Sniff out all the 'artificial intelligence' malarkyThis podcast is for both data scientists and business leaders of all kinds such as executives, directors, line of business managers, and consultants who are involved in or affected by the deployment of machine learning.To get machine learning to work, both the tech and business sides must make an effort to reach across wide chasm.About the host:Eric Siegel, Ph.D., is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series and its new sister, Generative AI Applications Summit, the instructor of the acclaimed online course 'Machine Learning Leadership and Practice End-to-End Mastery,' executive editor of The Machine Learning Times, and a frequent keynote speaker. He wrote the bestselling 'Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die,' which has been used in courses at hundreds of universities, as well as 'The AI Playbook: Mastering the Rare Art of Machine Learning Deployment.' Eric's interdisciplinary work bridges the stubborn technology/business gap. At Columbia, he won the Distinguished Faculty award when teaching the graduate *computer science* courses in ML and AI. Later, he served as a *business school* professor at UVA Darden. Eric has appeared on numerous media channels, including Bloomberg, National Geographic, and NPR, and has published in Newsweek, HBR, SciAm blog, WaPo, WSJ, and more.https://www.machinelearningweek.comhttp://www.bizML.comhttp://www.machinelearning.courseshttp://www.thepredictionbook.com more