What are the biggest challenges currently facing data security and privacy? What does the GDPR mean for civilians, working data scientists and businesses around the world? Is data anonymization actually possible or a pipe dream? Find out in Hugo's conversation with Katharine Jarmul, a data scientist, consultant, educator and co-founder of KI protect, a company that provides real-time protection for your data infrastructure, data science and AI. Links from the show KI Protect, providing real-time protection for your data infrastructure. What is GDPR? The summary guide to GDPR compliance in the UK by Matt Burgess for Wired Apple's differential privacy approach For more, see our page here

Why are spreadsheets ubiquitous in data analytics, why are so many data scientists anti-spreadsheet? Join Jenny Bryan, a software engineer at RStudio & recovering biostatistician who takes special delight in eliminating the small agonies of data analysis, and Hugo to discover why spreadsheets are in fact necessary in data analytics and how spreadsheet workflows can be incorporated into more general data science flows in sustainable and healthy ways. Welcome to the future. Links from the show Best Practices for Using Google Sheets in Your Data Project Jenny Bryan's repository of scary Excel stories Sanesheets, a self-proclaimed > by Jenny Bryan DataCamp's first two free courses on spreadsheets

Community building is an essential aspect of data science. But how do you do it? Find out in Hugo's conversation with Jared Lander, organizer of the New York Open Statistical Programming Meetup and the New York R Conference. Jared is also the Chief Data Scientist of Lander Analytics, a data science consultancy based in New York City and an Adjunct Professor of Statistics at Columbia University. How does Jared think about creating safe and welcoming spaces for budding and practicing data scientists of all ilk? How does he put this into practice? How does he make people feel comfortable and at home in a field in which so many intelligent and curious people feel like imposters? What practical & specific considerations are there in creating this home for underrepresented groups? How does he stay ahead of the curve in terms of modern, up-to-date content and speakers for his meetup and conference?

"Cloud computing is a huge revolution in the computing space, and it's also probably going to be one of the most transformative technologies that any of us experience in our lifetime. " Paige Bailey, Senior Cloud Developer Advocate at Microsoft, in this episode of DataFramed. In this conversation with Hugo, Paige reports from the frontier of cloud-based data science technologies, having just been at the Microsoft Build and Google I/O conferences. What is the future of data science in the cloud? How can you get started? Stick around to find out and much, much more.

What do online experiments, data science and product development look like at Booking.com, the world’s largest accommodations provider? Join Hugo's conversation with Lukas Vermeer to find out. Lukas is responsible for experimentation at Booking in the broadest sense of the word: from Infrastructure and Tools used to run experiments, Methodology and Metrics that help people make decisions to Training and Culture that help people understand what to do. They'll be talking about how Booking leverages Data Science to help empower people to experience the world through the three pillars of exploratory analysis, qualitative research and quantitative studies. They'll also take a deep dive into the fact that data science isn't actually anywhere near as objective as you may think.

Building models of the world is dangerous and there are pitfalls everywhere, even down to the assumptions that you make. To find out about many statistical pitfalls, and how to build more robust data scientific models using statistical modeling, whether it be in tech, epidemiology, finance or anything else, join Hugo's chat with Michael Betancourt, a physicist, statistician and one of the core developers of the open source statistical modeling platform Stan.

How can data science help in the fight against cancer? What are its limitations? Find out in this conversation from the frontier of research. Hugo speaks with Sandy Griffith from Flatiron Health, a healthcare technology and services company focused on accelerating cancer research and improving patient care. Sandy is Principal methodologist on Flatiron's Quantitative Sciences team and is tasked with leveraging data science "To improve lives by learning from the experience of every cancer patient".

Anthony Goldbloom, CEO of Kaggle, speaks with Hugo about Kaggle, data science communities, reproducible data science, machine learning competitions and the future of data science in the cloud. If you thought that Kaggle was merely a platform for machine learning competitions, you have to check out this chat, because these ML comps account for less than a third of activity on Kaggle today. In the discussion: Kaggle kernels for reproducible data science and the evolution of the Kaggle public data platform; the genesis of Kaggle and how Anthony managed to solve the cold start problem of building a two-sided market place; the exciting implications of Kaggle's recent acquisition by Google for the future of cloud-based data science; why Python is dominant on Kaggle.

"We should be looking at Automated Machine Learning tools as more like data science assistants, rather than replacements for data scientists" -- Randy Olson, Lead Data Scientist at Life Epigenetics, Inc. Randy specializes in artificial intelligence, machine learning, and created TPOT, a Data Science Assistant and a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. Will the future of data science be automated? Which verticals will experience the largest disruption? What will the role of data science become? There's one way to find out: jump straight into this chat with Randy and Hugo.

Michelle Gill, a deep learning expert at NVIDIA, an Artificial Intelligence company that builds GPUs, the processors that everybody uses for deep learning, speaks with Hugo about the modern superpower of deep learning and where it has the largest impact, past, present and future, filtered through the lens of Michelle's work at NVIDIA. Where is the modern superpower of deep learning most effective? Where is it not? Where should we channel our skepticism of the hype surrounding it?

Sebastian Raschka, a machine learning aficionado, data analyst, author, python programmer, open source contributor, computational biologist, and occasional blogger, speaks with Hugo about the role of data science in modern biology and the power of deep learning in today's rapidly evolving data science landscape. How is Sebastian using deep learning to build facial recognition software that also prevents racial and gender profiling? Check out this week's episode to find out.

Drew Conway, world-renowned data scientist, entrepreneur, author, speaker and creator of the Data Science Venn Diagram speaks with Hugo about how to build data science teams, along with the unique challenges of building data science products for industrial users. How does Drew now view the Venn circles he created, those of hacking skills, mathematical and statistical knowledge and substantive expertise, when building out data science teams?

Fake news: how can data science and deep learning be leveraged to detect it? Come on a journey with Mike Tamir, Head of Data Science at Uber ATG, who is building out a data science product that classifies text as news, editorial, satire, hate speech and fake news, among others. We'll also see what types of unique challenges Mike faced in his work at Takt, using data science to service the needs of Fortune 500 companies such as Starbucks.Links from the show FROM THE INTERVIEW FakerFact(Chrome Extension)FakerFact (Firefox Extension)FakerFact The Unreasonable Effectiveness of Recurrent Neural Networks by Andrei Karpathy FROM THE SEGMENTS The Double-edged Sword of Impact Parts I & 2 (with Friederike Schüür, Cloudera Fast Forward Labs) Media Manipulation and Disinformation Online from Data & SocietyJames Bridle's blog post 'Something is wrong on the internet'The Cost of Fairness in Binary Classification (.pdf), a paper by Menon & Williamson (2018)Multisided Fairness for Recommendation, a paper by Burke (2017)All The Cool Kids, How Do They Fit In? Popularity and Demographic Biases in Recommender Evaluation and Effectiveness, a paper by Ekstrand et al. (2018)The spread of true and false news online, a paper by Vosoughi et al. (2018) Original music and sounds by The Sticks.

Nuclear engineering, data science and open source software development: where do these all intersect? To find out, join Hugo and Katy Huff, Assistant Professor in the Department of Nuclear, Plasma, and Radiological Engineering at the University of Illinois where she leads the Advanced Reactors and Fuel Cycles research group.

How does data science help Buzzfeed achieve online virality? What type of mass online experiments do data scientists at BuzzFeed run for this purpose? What products do they develop to make all of this easy and intuitive for content producers? Find out about all of this and more in this episode when Hugo talks with Adam Kelleher, Principal Data Scientist at BuzzFeed and Adjunct Assistant Professor at Columbia University. They'll also dive into the role of thinking about causality in modern data science.

Air pollution, the environment and data science: where do these intersect? Find out in this episode of DataFramed, in which Hugo speaks with Roger Peng, Professor in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health, co-director of the Johns Hopkins Data Science Lab and co-founder of the Johns Hopkins Data Science Specialization. Join our discussion about data science, it's role in researching the environment and air pollution, massive open online courses for democratizing data science and much more.

Etsy, online experiments and data science are the topics of this episode, in which Hugo speaks with Emily Robinson, a data analyst at Etsy. How are data science and analysis integral to their business and decision making? Join us to find out. We'll also dive into the types of statistical modeling that occurs at Etsy and the importance of both diversity and community in data science.

Jake VanderPlas, a data science fellow at the University of Washington's eScience Institute, astronomer, open source beast and renowned Pythonista, joins Hugo to speak about data science, astronomy, the open source development world and the importance of interdisciplinary conversations to data science.

Airbnb's business depends on data science. In this episode, Hugo speaks with Robert Chang, data scientist at airbnb and previously at twitter. We'll be chatting about the different types of roles data science can play in digital businesses such as airbnb and twitter, how companies at different stages of development actually require divergent types of data science to be done, along with the different models for how data scientists are placed within companies, from the centralized model to the embedded to the hybrid: can you guess which is Robert's favourite? This is a hands-on, practical look at how data science works at airbnb and digital businesses in general.

The trucking industry is being revolutionized by Data Science. And how? Hugo speaks with Ben Skrainka, a data scientist at Convoy, a company that provides trucking services for shippers and carriers powered by technology to drive reliability, transparency, efficiency, and insights. We'll dive into how data science can help to achieve such a trucking revolution, and how this will impact all of us, from truckers to businesses and consumers alike. Along the way, we'll delve into Ben's thoughts on best practices in data science, how the field is evolving and how we can all help to shape the future of this emerging discipline.

Claudia Perlich, Chief Scientist at DStillery, a role in which she designs, develops, analyzes and optimizes the machine learning algorithms that drive digital advertising, speaks with Hugo about the role of data science in the online advertising world, the predictability of humans, how her team builds real time bidding algorithms and detects bots online, along with the ethical implications of all of these evolving concepts.

Chris Volinsky, AT&T Labs' Assistant Vice President for Big Data Research and a member of the team that won the $1M Netflix Prize, an open competition for improving Netflix' online recommendation system, speaks with Hugo. We'll be discussing the role data science plays in the modern telecommunications network landscape, how it helps a company that services over 140 million customers and what statistical and data scientific techniques his team uses to work with such large amounts of data. Along the way, we'll dive into the need for more transparency concerning the use of civilian data and Chris's work on the Netflix recommendation system prize.

Maelle Salmon, a data scientist who has worked in public health, both in infectious disease and environmental epidemiology, joins Hugo for a chat about the role of data science, statistics and data management in researching the health effects of air pollution and urbanization. In the process, we'll dive into the continual need for open source toolbox development, open data, knowledge organisation and diversity in this emerging discipline.

David Robinson, a data scientist at Stack Overflow, joins Hugo to speak about the evolving importance of citizen data science and a future in which data literacy is considered a necessary skill to navigate the world, similar to literacy today. We'll speak about many of Dave projects, including his analysis of Trump's tweets that demonstrated the stark contrast between Trump's own tweets and those of his PR machine. We'll also speak about ways for journalists, software engineers, scientists and all walks of life to get up and running doing data science and analysis.