In this episode I have an amazing conversation with Lillian Pearson from data-mania.com This is an action-packed episode on how data professionals can quickly convert their data expertise into high-growth data businesses, all by selecting optimal business models, revenue models, and pricing structures. If you want to know more or get in touch with Lillian, follow the links below: Weekly Free Trainings: We currently publish 1 free training per week on YouTube! https://www.youtube.com/channel/UCK4MGP0A6lBjnQWAmcWBcKQ Becoming World-Class Data Leaders and Data Entrepreneurs Facebook Group: https://www.facebook.com/groups/data.leaders.and.entrepreneurs LinkedIn: https://www.linkedin.com/in/lillianpierson/ The Data Entrepreneur’s Toolkit: A recommendation set for 32 free (or low-cost) tools & processes that'll actually grow your data business (even if you still haven’t put up that website yet!). https://www.data-mania.com/data-entrepreneur-toolkit/ 

Data Science at Home

Building high-growth data businesses with Lillian Pearson (Ep. 149)

Is there a gap between life sciences and data science? What's the situation when it comes to interdisciplinary research? In this episode I am with Laura Harris, Director of Training for the Institute of Cyber-Enabled Research (ICER) at Michigan State University (MSU), and we try to answer some of those questions.   You can contact Laura at training@msu.edu or on LinkedIn

Learning and training in AI times (Ep. 148)

In this episode I am with George Hosu from Cerebralab and we speak about how dangerous it is not to pay for the services you use, and as a consequence how dangerous it is letting an algorithm decide what you like or not.   Our Sponsors This episode is supported by Chapman’s Schmid College of Science and Technology, where master’s and PhD students join in cutting-edge research as they prepare to take the next big leap in their professional journey. To learn more about the innovative tools and collaborative approach that distinguish the Chapman program in Computational and Data Sciences, visit chapman.edu/datascience   If building software is your passion, you’ll love ThoughtWorks Technology Podcast. It’s a podcast for techies by techies. Their team of experienced technologists take a deep dive into a tech topic that’s piqued their interest — it could be how machine learning is being used in astrophysics or maybe how to succeed at continuous delivery.   Links https://cerebralab.com https://www.eugenewei.com/blog/2019/2/19/status-as-a-service 

You are the product [RB] (Ep. 147)

In this episode I speak with Ritchie Vink, the author of Polars, a crate that is the fastest dataframe library at date of speaking :) If you want to participate to an amazing Rust open source project, this is your change to collaborate to the official repository in the references.   References https://github.com/ritchie46/polars  

Polars: the fastest dataframe crate in Rust - with Ritchie Vink (Ep. 146)

Do you want to know the latest in big data analytics frameworks? Have you ever heard of Apache Arrow? Rust? Ballista? In this episode I speak with Andy Grove one of the main authors of Apache Arrow and Ballista compute engine. Andy explains some challenges while he was designing the Arrow and Ballista memory models and he describes some amazing solutions.   Our Sponsors This episode is supported by Chapman’s Schmid College of Science and Technology, where master’s and PhD students join in cutting-edge research as they prepare to take the next big leap in their professional journey. To learn more about the innovative tools and collaborative approach that distinguish the Chapman program in Computational and Data Sciences, visit chapman.edu/datascience   If building software is your passion, you’ll love ThoughtWorks Technology Podcast. It’s a podcast for techies by techies. Their team of experienced technologists take a deep dive into a tech topic that’s piqued their interest — it could be how machine learning is being used in astrophysics or maybe how to succeed at continuous delivery.   References   https://arrow.apache.org/   https://ballistacompute.org/   https://github.com/ballista-compute/ballista        

Apache Arrow, Ballista and Big Data in Rust with Andy Grove (Ep. 145)

Pandas is the de-facto standard for data loading and manipulation. Python is the de-facto programming language for such operations. Rust is the underdog. Or is it? In this episode I am showing you why that is no longer the case.   Our Sponsors This episode is supported by Chapman’s Schmid College of Science and Technology, where master’s and PhD students join in cutting-edge research as they prepare to take the next big leap in their professional journey. To learn more about the innovative tools and collaborative approach that distinguish the Chapman program in Computational and Data Sciences, visit chapman.edu/datascience   Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and secure data with higher transparency and disintermediation, and build the statistical models that will support your business.     Useful Links https://github.com/haixuanTao/Data-Manipulation-Rust-Pandas https://github.com/ritchie46/polars https://github.com/rust-ndarray/ndarray  

Pandas vs Rust (Ep. 144)

In plain English, concurrent and parallel are synonyms. Not for a CPU. And definitely not for programmers. In this episode I summarize the ways to parallelize on different architectures and operating systems. Rock-star data scientists must know how concurrency works and when to use it IMHO.   Our Sponsors This episode is supported by Chapman’s Schmid College of Science and Technology, where master’s and PhD students join in cutting-edge research as they prepare to take the next big leap in their professional journey. To learn more about the innovative tools and collaborative approach that distinguish the Chapman program in Computational and Data Sciences, visit chapman.edu/datascience   Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and secure data with higher transparency and disintermediation, and build the statistical models that will support your business.     Useful Links http://web.mit.edu/6.005/www/fa14/classes/17-concurrency/ https://doc.rust-lang.org/book/ch16-00-concurrency.html https://urban-institute.medium.com/using-multiprocessing-to-make-python-code-faster-23ea5ef996ba  

Concurrent is not parallel - Part 2 (Ep. 143)

In plain English, concurrent and parallel are synonyms. Not for a CPU. And definitely not for programmers. In this episode I summarize the ways to parallelize on different architectures and operating systems. Rock-star data scientists must know how concurrency works and when to use it IMHO.   Our Sponsors This episode is supported by Chapman’s Schmid College of Science and Technology, where master’s and PhD students join in cutting-edge research as they prepare to take the next big leap in their professional journey. To learn more about the innovative tools and collaborative approach that distinguish the Chapman program in Computational and Data Sciences, visit chapman.edu/datascience   Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and secure data with higher transparency and disintermediation, and build the statistical models that will support your business.      

Concurrent is not parallel - Part 1 (Ep. 142)

This is one of the most dynamic and fascinating topics: API technologies for machine learning. It's always fun to build ML models. But how about serving them in the real world? In this episode I speak about three must-know technologies to place your model behind an API.   Our Sponsors This episode is supported by Chapman’s Schmid College of Science and Technology, where master’s and PhD students join in cutting-edge research as they prepare to take the next big leap in their professional journey. To learn more about the innovative tools and collaborative approach that distinguish the Chapman program in Computational and Data Sciences, visit chapman.edu/datascience   If building software is your passion, you’ll love ThoughtWorks Technology Podcast. It’s a podcast for techies by techies. Their team of experienced technologists take a deep dive into a tech topic that’s piqued their interest — it could be how machine learning is being used in astrophysics or maybe how to succeed at continuous delivery.

Backend technologies for machine learning in production (Ep. 141)

In this episode I am with George Hosu from Cerebralab and we speak about how dangerous it is not to pay for the services you use, and as a consequence how dangerous it is letting an algorithm decide what you like or not.   Our Sponsors This episode is supported by Chapman’s Schmid College of Science and Technology, where master’s and PhD students join in cutting-edge research as they prepare to take the next big leap in their professional journey.To learn more about the innovative tools and collaborative approach that distinguish the Chapman program in Computational and Data Sciences, visit chapman.edu/datascience   If building software is your passion, you’ll love ThoughtWorks Technology Podcast. It’s a podcast for techies by techies. Their team of experienced technologists take a deep dive into a tech topic that’s piqued their interest — it could be how machine learning is being used in astrophysics or maybe how to succeed at continuous delivery.   Links https://cerebralab.com https://www.eugenewei.com/blog/2019/2/19/status-as-a-service 

You are the product (Ep. 140)

 The financial system is changing. It is becoming more efficient and integrated with many more services making our life more... digital. Is the old banking system doomed to fail? Or will it just be disrupted by the smaller players of the fintech industry?In this episode we answer some of these fundamental questions with Alessandro E. Hatami from Pacemakers Subscribe to the Newsletter and come chat with us on the official Discord channel   Our Sponsors This episode is supported by Chapman’s Schmid College of Science and Technology, where master’s and PhD students join in cutting-edge research as they prepare to take the next big leap in their professional journey.To learn more about the innovative tools and collaborative approach that distinguish the Chapman program in Computational and Data Sciences, visit chapman.edu/datascience   Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and secure data with higher transparency and disintermediation, and build the statistical models that will support your business.    

How to reinvent banking and finance with data and technology (Ep. 139)

Have you clicked the button? Accepted the new terms? It's time we have a talk.

What's up with WhatsApp? (Ep. 138)

In this podcast I get inspired by Paul Done's presentation about The Six Principles for Building Robust Yet Flexible Shared Data Applications, and show how powerful of a language Rust is while still maintaining the flexibility of less strict languages.   Our Sponsor This episode is supported by Chapman’s Schmid College of Science and Technology, where master's and PhD students join in cutting-edge research as they prepare to take the next big leap in their professional journey. To learn more about the innovative tools and collaborative approach that distinguish the Chapman program in Computational and Data Sciences, visit chapman.edu/datascience  

Is Rust flexible enough for a flexible data model? (Ep. 137)

In this episode I explain the basics of computer architecture and introduce some features of the Apple M1 Is it good for Machine Learning tasks?   References Computer architectures book https://www.amazon.com/Computer-Architecture-Quantitative-John-Hennessy/dp/012383872X Performance https://nod.ai/comparing-apple-m1-with-amx2-m1-with-neon/ 

Is Apple M1 good for machine learning? (Ep.136)

In this episode I speak with Daniel McKenna about Rust, machine learning and artificial intelligence. You can find Daniel from http://github.com/xd009642  https://twitter.com/xd009642   Don't forget to come join me in our Discord channel speaking about all things data science. Subscribe to the official Newsletter and never miss an episode

Rust and deep learning with Daniel McKenna (Ep. 135)

Technology, machine learning and algorithms. Come join the discussion! https://discord.gg/4UNKGf3

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Data Science at Home

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