About DataHack Radio
TensorFlow is easily the most widely used deep learning framework right now. The idea behind TensorFlow (TF) has even spawned multiple products, such as TensorFlow.js, Swift for TensorFlow, TensorFlow Lite, among other things. And who better to talk about that, plus all things TensorFlow, than TF's very own Product Manager? We are delighted to welcome Paige Bailey on the latest episode of the DataHack Radio podcast! Read more about the podcast and get free resources here: https://www.analyticsvidhya.com/blog/2019/09/all-you-need-to-know-about-tensorflow-google-paige-bailey
Chatbots are the most common application of Natural Language Processing (NLP). Rasa is an open source framework that we can leverage to build our own chatbots. So we are delighted to have Rasa's data scientist and Head of Developer Relations, Justina Petraitytė, on our DataHack Radio podcast! Read more here:https://www.analyticsvidhya.com/blog/2019/07/exploring-designing-chatbots-rasa-justina-petraityte
We are delighted to welcome Ines Montani and Matt Honnibal, the developers of spaCy - a powerful and advanced library for NLP. Everything you've ever wanted to know about the wonderful spaCy library is right here in the latest DataHack Radio podcast. Highlights of topic covered: - The idea behind developing spaCy - spaCy's awesome evolution from the first alpha release to the current version 2.1 - Use cases of spaCy including a couple of surprising applications - Ines and Matt's advice to NLP enthusiasts Read the full article here: https://www.analyticsvidhya.com/blog/2019/05/datahack-radio-ines-montani-matthew-honnibal-brains-behind-spacy
How do computer vision techniques work in an industry setting? How does an organization use data engineering to scale up its operations? These are questions every aspiring data scientist must be aware of. Dat Tran, Head of Data Science at idealo internet GmbH, is the perfect person to shed light on these questions. Read more about this podcast: https://www.analyticsvidhya.com/blog/2019/04/datahack-radio-exploring-computer-vision-data-engineering-podcast-dat-tran
Fake news is one of the biggest scourges in our digitally connected world. Can machine learning make a difference? We are thrilled to have Mike Tamir, Ph.D., on this episode as he talks about using ML to separate truth from fiction using his research project called FakerFact. Read more here: https://www.analyticsvidhya.com/blog/2019/04/datahack-radio-machine-learning-identify-fake-news-mike-tamir
How do we build interpretable machine learning models? Or, in other words, how do we build trust in the models we design? This is such a critical question in every machine learning project. We need to find a way to use these powerful ML algorithms and still make them work in business setting. So in this episode #20 of our DataHack Radio podcast, we welcome Christoph Molar, author of the popular book - "Interpretable Machine Learning". Who better to talk about this fundamental and critical topic? Read more here: https://www.analyticsvidhya.com/blog/2019/03/datahack-radio-interpretable-machine-learning-christoph-molnar
How close are we to Artificial General Intelligence (AGI)? It seems we take a step closer to that reality with every breakthrough. And yet, it feels far too away in the future. Why are we so far away from AGI despite the unabated rise in computational hardware? What's holding us back from programming machines that generalize to multiple domains? We invited Professor Melanie Mitchell to answer these pertinent and pressing questions in episode #19 of the DataHack Radio podcast. Read more about the episode here: https://www.analyticsvidhya.com/blog/2019/03/datahack-radio-19-the-path-to-artificial-general-intelligence-with-professor-melanie-mitchell
In this episode, we talk to Andriy Burkov, Machine Learning Team Leader at Gartner and author of the Hundred-Page Machine Learning Book. The book has quickly ascended the bestseller list and is perched at #1 on Amazon (under the 'machine learning' category). The book has even been endorsed by the great Peter Norvig! Kunal and Andriy talk about this and much more in this episode! Read more here -https://www.analyticsvidhya.com/blog/2019/02/datahack-radio-hundred-page-machine-learning-book-andriy-burkov
In this podcast, Kunal speaks to Professor Ravi about his background, his interest and research in reinforcement learning, and the intricacies and nuances of this field. Professor B. Ravindran has an incredibly rich background in academic research, headlined by his work in reinforcement learning. His Google Scholar profile shows his research papers have been cited over 2,200+ times! Read the podcast notes here: https://www.analyticsvidhya.com/blog/2019/02/datahack-radio-reinforcement-learning-professor-balaraman-ravindran/
SRK is an inspiration and enigma in the data science community. Whether it's his analytical acumen, wealth of experience, or down-to-earth demeanour, we could all learn something from him. In this episode, we cover: - SRK's background and his first brush with analytics - His transition into data science - The advantages of participating in data science competitions - How competitions help in a day-to-day industry role - Advice to aspiring data scientists from a Kaggle Grandmaster Read more here: https://www.analyticsvidhya.com/blog/2019/01/datahack-radio-tips-crack-data-science-competitions-kaggle-grandmaster/
Reinforcement learning algorithms have been knocking on the door of industrial applications in recent years. Will they finally blow the door wide open in 2019? What are some of the biggest obstacles holding back reinforcement learning? And is there a ceiling we can put on where RL will take us in the future? We welcome 2019 on DataHack Radio with a stellar episode #15 featuring Xander Steenbrugge, as he navigates us through the wide-ranging and intricate world of reinforcement learning. And yes, those above questions have been very expertly handled in this episode. Read more about this episode here: https://www.analyticsvidhya.com/blog/2019/01/datahack-radio-reinforcement-learning-xander/
Quantum computing and quantum machine learning - most of us have come across these concepts at some point without getting the opportunity to delve deeper. But what if I told you that these could potentially disrupt the way we see and use technology? We are joined by Dr. Mandaar Pande in episode #14 of the DataHack Radio podcast, where he navigates us through the wonderfully complex world of quantum computing.
Did you know that the oil and gas industry is currently only using close to 1% of the data it generates? A mind-boggling figure, and not one we usually think about when talking about artificial intelligence and machine learning applications. In episode #13 of the DataHack Radio podcast, we are joined by Yogendra Narayan Pandey, Ph.D, as he takes us on a knowledge-rich journey in the world of oil and gas.
We see a ton of aspiring data scientists interested in this field, but they often turn away daunted by the challenges NLP presents. It's such a niche line of work, and we at Analytics Vidhya would love to see more of our community actively participate in ground-breaking work in this field. So we thought what better way to do this than get an NLP expert on our DataHack Radio podcast? Yes, we've got none other than Sebastian Ruder in Episode 12! This podcast is a knowledge goldmine for NLP enthusiasts, so make sure you tune in.
What is decision intelligence? How does it tie into the world of data science? And what does Google have to do with it all? Click on the above SoundCloud link and find out! Welcome to episode #11 of DataHack Radio, where we were joined by Google Cloud's Chief Decision Scientist, Cassie Kozyrkov! Cassie is a well-known speaker in the data science sphere, and often pens down her thoughts in articulate fashion in this field. She takes us on a journey into her life at Google and how she went from being a Statistician at Google to her current role.
Have you noticed that the recent surge of data scientists have a background in computer science? It's not a coincidence. These two domains are important in their own right but when merged together, they produce powerful results. We are thrilled to announce the release of episode 10 of our DataHack Radio podcast with none other than Professor Jeannette M. Wing! She has over 4 decades of experience in academia and the industry, and there is no one better to give a perspective on how computer science has evolved, and how it meshes with the data science world.
Airbnb and Lyft have transformed their respective industries in recent years using data science as their guiding light. In episode 9 of our DataHack Radio series, Dr. Alok Gupta gave us some very interesting insights into how Airbnb and Lyft use data science. For instance, did you know that Spark is Airbnb's machine learning tool of choice? You will learn a lot in this podcast about how a data science leader thinks about challenging problems, and how leading tech start-ups scale up their operations from the ground up.
How do self-driving cars work? How difficult is it making one from scratch? What kind of machine learning techniques are used? In this podcast, Drive.ai's co-founder Brody Huval sheds light on these questions, along with other really intriguing facets of autonomous vehicles. It's a podcast you better not miss!
Data science is still a very nascent field in India, despite the recent surge in interest. From agriculture to healthcare, there are a plethora of challenges the Government faces on a day-to-day basis, and that was the primary reason for founding a data science department under the NITI Aayog initiative. On this Independence Day, we thought what better way to acquaint our community with these challenges and how our Goverment is using data science to tackle them, than bring NITI Aayog's Head of Data Science straight to you? Dr.Avik spoke about various topics, from his love of mathematics to his master's and Ph.D thesis techniques. He also provided details about the work performed by the data science team under the NITI Aayog initiative, a must-listen for all Indians.
Have you ever wondered how Coursera uses data science? Sure we have all taken (or heard of) their courses but how does the platform make use of the amount of data that's generated? How does their pricing strategy work for certificates? How is their data science team structured? What tools and techniques do they use? These are just some of the questions answered in this phenomenal podcast. We had the pleasure of hosting Coursera's Head of Data Science, Emily Glassberg Sands, who gave us a detailed and thorough explanation of how Coursera functions behind the scenes.