DataFramed

DataFramed

By DataCampTechnology
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DataFramed episodes

  • #17 Biology and Deep Learning
    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.
    59 min
  • #15 Building Data Science Teams
    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?
    1 hr
  • #13 Fake News Detection with Data Science

    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 & Society
    • James 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.

    59 min
  • #12 Data Science, Nuclear Engineering and the Open Source
    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.
    58 min
  • #11 Data Science at BuzzFeed and the Digital Media Landscape
    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.
    1 hr
  • #10 Data Science, the Environment and MOOCs
    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.
    55 min
  • #9 Data Science and Online Experiments at Etsy
    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.
    1 hr
  • #8 Data Science, Astronomy and the Open Source
    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.
    1 hr
  • #7 Data Science at Airbnb
    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.
    59 min
  • #2 How Data Science is Impacting Telecommunications Networks
    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.
    57 min

About DataFramed

From the publisher's feed

Data science and machine learning are making the impossible possible—whether it is awe-inspiring results from language models, or huge gains in computational biology. However, as data science is…