In today's fast-paced world, podcasts have proved to be an incredibly great source of learning for data scientists who are willing to learn more from all the possible resources available. Alongside, amid COVID, when the majority of data professionals are working from home, podcasts are turning out to be an excellent way to not only upskill themselves but also to pass leisure time. Not only AI and data science podcasts would help these professionals to be updated with latest trends and researches but also help them in understanding the core working of various data science applications. Furthermore, many of these data science podcasts also invite some of the renowned minds of the industry for data science professionals to gain more understanding of this industry. COVID lockdown can be monotonous and daunting for many, and thus to make good use of the leisure time, data scientists can get their hands on some of the informative and exciting AI and data science podcasts.
Podcasts are excellent for keeping up with the dope in your field and also familiarise with the processes/people behind the scenes. Following are five of the podcasts which I personally think are the best (in no particular order) by virtue of their content and quality of guests/hosts. This is hosted by Lukas Biewald who is heavy on startup creds -- he is the founder & CEO of Weights & Biases, a company that builds developer tools for ML. He also founded Figure Eight, an AI/ML company that was sold for $300 million. Lukas is known for prying out details on technology and engineering practices at organisations his guests are associated with.
Talking Machines podcasts feature conversations in today's popular areas of machine learning. They appeal to both machine learning professionals and enthusiasts. Talks are usually about NIPS (Neural Computing Systems), and guests are usually top practitioners. Data Skeptic explains certain concepts in data science in short sections. Longer interviews with practitioners and experts on interesting data-related topics are also included.
It seems like AI, data science, machine learning and bots are some of the most discussed topics in tech today. My preferred way to do this is always through listening to podcasts. Here are the ones I've found the most interesting: They alternate between great interviews with academics & practitioners and short 10–15 minute episodes where the hosts give a short primer on topics like calculating feature importance, k-means clustering, natural language processing and decision trees, often using analogies related to their pet parrot, Yoshi. This is the only place where you'll learn about k-means clustering via placement of parrot droppings. Hosted by Katie Malone and Ben Jaffe, this weekly podcast covers diverse topics in data science and machine learning: talking about specific concepts like model theft and the cold start problem and how they apply to real-world problems and datasets.