Tag Data Science

Deep Learning Hardware with Xin Wang

http://traffic.libsyn.com/sedaily/2018_01_29_DeepLearningHardware.mp3Podcast: Play in new window | Download Training a deep learning model involves operations over tensors. A tensor is a multi-dimensional array of numbers. For several years, GPUs were used for these linear algebra calculations. That’s because graphics chips are built to efficiently process matrix operations. Tensor processing consists of linear algebra operations that are similar in some ways to graphics processing–but not identical. Deep learning workloads do not run

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Machine Learning and Technical Debt with D. Sculley Holiday Repeat

http://traffic.libsyn.com/sedaily/ml_techdebt_ad_free.mp3Podcast: Play in new window | DownloadOriginally published November 17, 2015 “Changing anything changes everything.” Technical debt, referring to the compounding cost of changes to software architecture, can be especially challenging in machine learning systems. D. Sculley is a software engineer at Google, focusing on machine learning, data mining, and information retrieval. He recently co-authored the paper Machine Learning: The High Interest Credit Card of Technical Debt. Questions How do

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Data Science Mindset with Zacharias Voulgaris

http://traffic.libsyn.com/sedaily/DataScienceMindset.mp3Podcast: Play in new window | Download A company’s approach to data can make or break the business. In the past, data was static. There was not much data, it sat in Excel, and it was interacted with on a nightly or monthly basis. Now, data is dynamic, real time and huge. To tap into available data, many industries have oriented themselves to becoming data intensive. With many new industry

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Go Data Science with Daniel Whitenack

http://traffic.libsyn.com/sedaily/Go_Data_Science.mp3Podcast: Play in new window | Download Data science is typically done by engineers writing code in Python, R, or another scripting language. Lots of engineers know these languages, and their ecosystems have great library support. But these languages have some issues around deployment, reproducibility, and other areas. The programming language Golang presents an appealing alternative for data scientists. Daniel Whitenack transitioned from doing most of his data science work

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Winning With Data with Tomasz Tunguz

http://traffic.libsyn.com/sedaily/winningwithdata_edited_2.mp3Podcast: Play in new window | Download Large technology companies have no shortage of data. But raw data itself does not provide a competitive advantage. Many companies are bottlenecked by a shortage of data scientists who can query that data effectively. This results in an organizational dysfunction where people lining up to ask questions of the data science team are unable to move as fast as they want to. Tomasz

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Simpsons Data Science with Todd Schneider

http://traffic.libsyn.com/sedaily/simpsons_data_science_edited.mp3Podcast: Play in new window | Download The Simpsons is a classic, beloved television show. The scripts of The Simpsons have been made publicly available, and include dialogue, location, and character information. Todd Schneider used these scripts and other information sources as a corpus to analyze The Simpsons and find interesting statistics–such as who the most important supporting characters were, and how the ratings of the show have trended over

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PANCAKE STACK Data Engineering with Chris Fregly

http://traffic.libsyn.com/sedaily/pancakestack_edited_fixed.mp3Podcast: Play in new window | Download Data engineering is the software engineering that enables data scientists to work effectively. In today’s episode, we explore the different sides of data engineering–the data science algorithms that need to be processed and the implementation of software architectures that enable those algorithms to run smoothly. The PANCAKE STACK is a 12-letter acronym that Chris Fregly gave to a collection of data engineering technologies

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Data Validation with Dan Morris

http://traffic.libsyn.com/sedaily/datavalidation_edited_2.mp3Podcast: Play in new window | Download Data Validation is the process of ensuring that data is accurate. In many software domains, an application is pulling in large quantities of data from external sources. That data will eventually be exposed to users, and it needs to be correct. Radius Intelligence is a company that aggregates data on small businesses. In order to ensure that business addresses and phone numbers are

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Using Software to Discover Rare Diseases with Matt Might

http://traffic.libsyn.com/sedaily/Might_Edited_2.mp3Podcast: Play in new window | Download “In many ways, nature is still the fastest computer we have when it comes to studying disease.” Software engineering is a deterministic field. We write lines of code, and feed data into that code, expecting to get a certain answer. Computing is deterministic because humans developed it–we understand computers from top to bottom. The same cannot be said about biology. Matt Might is

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Data Visualization and Mapping with Aurelia Moser

http://traffic.libsyn.com/sedaily/Mapping_Edited.mp3Podcast: Play in new window | Download “I’m always worried that if you teach too much magic, people don’t learn the basics – they don’t know why something is working, they just know the documentation said it should work that way.” On Software Engineering Daily, we often discuss big data in terms of data engineering and data science. Data engineering is the infrastructure and pipelines that handle massive amounts of

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Machine Learning in Healthcare with David Kale

http://traffic.libsyn.com/sedaily/healthcareML_Edited.mp3Podcast: Play in new window | Download “Building a model to predict disease and deploying that in the wild – the bar for success is much higher there than, say, deciding what ad to show you.” Diagnosing illness today requires the trained eye of a doctor. With machine learning, we might someday be able to diagnose illness using only a data set. Today on Software Engineering Daily, we are joined

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Data Science at Monsanto with Tim Williamson

http://traffic.libsyn.com/sedaily/Monsanto_Edited_FInal.mp3Podcast: Play in new window | Download “Nothing’s cool unless you call it ‘as a service.’ ” Monsanto is a company that is known for its chemical and biological engineering. It is less well known for its data science and software engineering teams. Tim Williamson is a data scientist at Monsanto, and on today’s show he talked about how he and a small group of engineers at Monsanto dramatically shifted

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Matplotlib with Ben Root

“My eyes just roll whenever I see a table just full of numbers – they don’t mean anything to me, I don’t immediately grok it. But if I see a line plot, I get it, right away.”

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Deep Learning and Keras with François Chollet

“I definitely think we can try to abstract away the first principles of intelligence and then try to go from these principles to an intelligent machine that might look nothing like the brain.”

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Mesosphere and Tech Journalism with Derrick Harris

“The business of technology and the technology of technology are kind of converging if you ask me. And there is definitely a space for some publications that don’t have decades of technical debt in the software space.”

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Spark in Practice with Holden Karau

“I found Spark and I was really excited because I’m a functional programming nerd, and it was written in Scala.”

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Machine Learning for Businesses with Joshua Bloom

“You’ve got software engineers who are interested in machine learning, and think what they need to do is just bring in another module and then that will solve their problem. It’s particularly important for those people to understand that this is a different type of beast.”

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Data Science with Srini Kadamati

“I really think that data science is like design in the sense that it’s a way of thinking.”

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Hiring Engineers with Ammon Bartram

http://traffic.libsyn.com/sedaily/Triplebyte_Edited.mp3Podcast: Play in new window | Download “Humans are the most complicated thing out there – judging human skill is extremely hard, there’s all kinds of ways that people can be good.” Triplebyte is a technical hiring platform that vets engineers using a comprehensive evaluation platform and connects them to companies that are interesting in hiring them. Triplebyte was part of the Y Combinator summer class of 2015. Ammon Bartram

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TensorFlow with Greg Corrado

“You don’t mind if failures slow things down, but its very important that failures do not stop forward progress.”

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