Introducing Numerically Speaking: The Anaconda Podcast
Numerically Speaking: The Anaconda Podcast
Release Date: 06/22/2022
Data Engineering as a Scientific Tool
Numerically Speaking: The Anaconda Podcast
In this episode, host is joined by Dr. Patrick Kavanagh, an astrophysicist and software developer at the . Patrick works on the (JWST), helping to write code that allows scientists to interpret the raw data they receive from space. Patrick talks to Peter about cleaning telescope data sets to make them more scientifically useful, and more. Patrick’s team working on the Mid-Infrared Instrument on the JWST writes software in Python to help deliver science-ready data to astronomers and astrophysicists. Patrick’s work facilitates more precise study of distant stars and galaxies in a way that...
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Optimizing Python for Speed and Compatibility
Numerically Speaking: The Anaconda Podcast
In the penultimate episode of season one, host and , Software Engineer at (owned by Meta), discuss considerations around making Python faster while maximizing compatibility and performance. Several years ago, Carl and his team started working on a project called in an effort to improve CPU efficiency across Meta’s servers by “[optimizing] things at the level of Python runtime.” While initially meant to serve as a stop gap, Cinder yielded impressive wins that transformed it into a premier and ongoing project at Instagram. In addition to Cinder, Peter and Carl discuss: -...
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Climate Science, Scientific Computing, and Data Accessibility
Numerically Speaking: The Anaconda Podcast
This episode’s conversation between host Peter Wang and , Associate Professor at , explores climate science, scientific computing, data accessibility, and more. Topics that Peter and Ryan cover include: - Cloud computing - Open data and collaboration - Climate science and the private sector - Open-source projects like and Climate data is sometimes restricted in the way it flows between interested parties; the growth of private industry around data storage and dissemination has put up barriers to entry that can limit access to valuable systems and data. This is...
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Shaping Best Practices for Monitoring ML Models
Numerically Speaking: The Anaconda Podcast
In this episode, host is joined by , CEO and Co-Founder of . Peter and Elena discuss how Evidently AI’s open-source tooling is helping users monitor machine learning (ML) models, and why that’s important. Elena has found that Evidently AI’s open-source approach is attractive to data scientists and ML engineers who are ramping up model maintenance, retraining, and monitoring efforts. Peter and Elena also touch on: - On-premises versus cloud-based deployment - ML model monitoring best practices - The value of pipeline testing - And more! You can find a human-verified...
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Unifying and Accelerating Data Science, ML, and Advanced Analytics Workflows
Numerically Speaking: The Anaconda Podcast
In this episode, host speaks with , Director of Product Management at , about how Snowflake solutions support professionals in data science, machine learning, and advanced analytics. Torsten has worked with data throughout his entire career. At Snowflake, he focuses on Snowflake's data lake, data pipelines, and data science workloads, as well as Snowflake's developer and partner ecosystem. Thanks to the broader language compatibilities of Snowflake and its Snowpark library, data engineering is becoming more accessible beyond the SQL community. Torsten and Snowflake continue to work to unify...
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Autopoiesis in Systems of People and Machines
Numerically Speaking: The Anaconda Podcast
In “Autopoiesis in Systems of People and Machines,” welcomes . Paco is a Managing Partner at , a company that offers enterprise customers full-stack engineering for AI applications at scale, with an emphasis on open-source integrations. Paco forged a career in artificial intelligence when many people were skeptical of it and now boasts over 40 years of computer science experience. Peter and Paco discuss histories and frameworks that are impacting today’s systems of people and machines. Paco touches on corporate law and how long ago, the concept of insurance allowed for the...
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From “Enthusiastic User” to pandas Maintainer
Numerically Speaking: The Anaconda Podcast
On this episode of Numerically Speaking: The Anaconda Podcast, host welcomes pandas maintainer , Managing Director at . Jeff began his career on Wall Street in the 1990’s and used Perl for a long time. He developed an interest in Python in the 2000’s. He was then quickly drawn to pandas and began to spend his hour-long ferry commutes contributing to its open-source code. His contributions over the years have been significant, to say the least. When it comes to open source, says Peter, “my flame isn’t diminished by lighting your candle.” Cloning a copy of pandas, for...
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A Specialized Approach to Hardware
Numerically Speaking: The Anaconda Podcast
End users who are not schooled in hardware can often default to, “just give me something that works.” , Staff AI Engineer, Strategy & Vision for Data Science and AI Products at , understands this thinking but also believes that end users can be educated on the advantages of configuring their computer hardware to suit their specific needs. David advocates for using the right hardware for a given task—and that may mean different configurations and/or different machines for different tasks, rather than a one-size-fits-all solution. David and host also discuss: -...
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Human in the Loop
Numerically Speaking: The Anaconda Podcast
Machine learning (ML) has reached an exciting phase of development, a phase that , Senior ML Engineer at * has characterized as the “steam-powered days.” In this episode of Numerically Speaking: The Anaconda Podcast, Vicki talks about the state of the industry and where she sees things heading. Vicki’s discussion with host covers: The interplay between software engineering and ML, the human element of the development lifecycle (and the lack thereof in social media) and the operationalization and the rise of microservices. Resources: Click to visit...
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Software, Venture Capital, and the Future of Work
Numerically Speaking: The Anaconda Podcast
While today’s software may seem magical compared to that of previous generations, it still takes multiple software iterations to fold in new fundamental technologies. Joining us for this episode is , Partner at . Bloomberg Beta runs several seed-stage investment funds, with a particular interest in low-code/no-code/WebAssembly startups. In this episode, James and host discuss: - why it’s important to be humble when looking towards the future of software - why venture capitalists (VCs) shouldn’t be considered “Yodas” who can fix every problem - what James...
info_outlineIn this introductory episode of Numerically Speaking: The Anaconda Podcast, Anaconda CEO Peter Wang provides an overview of what to expect from this podcast.
Peter will be exploring a variety of topics within the dynamic world of data science, including quantitative computing, business, and entrepreneurship. Guests will include top data science experts as well as creators of cutting-edge open-source tools.
Whether you want to learn about AI, grow your data science career, or simply better understand the numbers and computers that shape our world, this podcast is for you.
We're excited to bring you insights about data science and the people that make it happen.
Be sure to subscribe to stay up to date with new episodes.
This episode is brought to you by Anaconda, the world's most popular data science platform. We are committed to increasing data literacy and providing data science technology for a better world. Anaconda is the best way to get started with, deploy, and secure Python data science software.
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- Peter Wang on Twitter - https://twitter.com/pwang
- Anaconda, Inc. on Twitter - https://twitter.com/anacondainc