Data Science at Home

Can I get paid for my data? With Mike Andi from Mytiki (Ep. 150)

Your data is worth thousands a year. Why aren’t you getting your fair share? There is a company that has a mission: they want you to take back control and get paid for your data.
In this episode I speak about knowledge graphs, data confidentiality and privacy with Mike Audi, CEO of MyTiki.
 
 
You can reach them on their website https://mytiki.com/
 
Discord official channel
https://discord.com/invite/evjYQq48Be
 
Telegram
https://t.me/mytikiapp
 
Signal
https://signal.group/#CjQKIA66Eq2VHecpcCd-cu-dziozMRSH3EuQdcZJNyMOYNi5EhC0coWtjWzKQ1dDKEjMqhkP
 
 

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

In this episode I have an amazing conversation with Lillian Pierson 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/

Learning and training in AI times (Ep. 148)

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

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

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

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

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
 

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

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
 
 
 
 

Pandas vs Rust (Ep. 144)

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
 

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.  
 
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 1 (Ep. 142)

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.  
 
 

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

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.