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/