DataTalks.Club

By DataTalks.ClubTechnology

DataTalks.Club episodes

October 21, 2022From Data Science to DataOps - Tomasz Hinc
We talked about:
Tomasz’s background

What Tomasz did before DataOps (Data Science)

Why Tomasz made the transition from Data science to DataOps

What is DataOps?

How is DataOps related to infrastructure?

How Tomasz learned the skills necessary to become DataOps

Becoming comfortable with terminal

The overlap between DataOps and Data Engineering

Suitable/useful skills for DataOps

Minimal operational skills for DataOps

Similarities between DataOps and Data Science Managers

Tomasz’s interesting projects

Confidence in results and avoiding going too deep with edge cases

Conclusion

Links:
Terminal setup video, 19 minutes long: https://www.youtube.com/watch?v=D2PSsnqgBiw

Command line videos, one and a half hour to become somewhat comfy with the terminal: https://www.youtube.com/playlist?list=PLIhvC56v63IKioClkSNDjW7iz-6TFvLwS

Course from MIT talking about just that (command line, git, storing secrets): https://missing.csail.mit.edu/

ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
52 min
October 14, 2022Data Science Career Development - Katie Bauer
We talked about:
Katie’s background

What is a data scientist?

What is a data science manager?

Quality of the craft

How data leaders promote career growth

Supporting senior data professionals

Choosing the IC route vs the management route

Managing junior data professionals

Talking to senior stakeholders and PMs as a junior

The importance of hiring juniors

What skills do data scientist managers need to get hired?

How juniors that are just starting out can set themselves apart from the competition

Asking senior colleagues for help and the rubber duck channel

The challenges of the head of data

Conclusion

Links:
Jobs at Gloss Genius: https://boards.greenhouse.io/glossgenius

ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
54 min
October 07, 2022From Testing Phones to Managing NLP Projects - Alvaro Navas Peire
We talked about:
Alvaro’s background

Working as a QA (Quality Assurance) engineer

Transitioning from QA to Machine Learning

Gathering knowledge about ML field

Searching for an ML job (improving soft skills and CV)

Data science interview skills

Zoomcamp projects

Zoomcamp project deployment

How to not undersell yourself during interviews

Alvaro’s experience with interviews during his transition

Alvaro’s Zoomcamp notes

Alvaro’s coach

The importance of mathematical knowledge to a transition into ML

Preparing for technical interviews

Alvaro’s typical workday

Alvaro’s team’s tech stack

The importance of a technical background to transitioning into ML

Links:
Alvaro's CV: https://www.dropbox.com/s/89hkt3ug0toqa2n/CV%20nou%20-%20angl%C3%A8s.pdf?dl=0

Github profile: https://github.com/ziritrion

LinkedIn profile: https://www.linkedin.com/in/alvaronavas/

ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcampJoin
DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
49 min
September 30, 2022Responsible and Explainable AI - Supreet Kaur
We talked about:
Supreet’s background

Responsible AI

Example of explainable AI

Responsible AI vs explainable AI

Explainable AI tools and frameworks (glass box approach)

Checking for bias in data and handling personal data

Understanding whether your company needs certain type of data

Data quality checks and automation

Responsibility vs profitability

The human touch in AI

The trade-off between model complexity and explainability

Is completely automated AI out of the question?

Detecting model drift and overfitting

How Supreet became interested in explainable AI

Trustworthy AI

Reliability vs fairness

Bias indicators

The future of explainable AI

About DataBuzz

The diversity of data science roles

Ethics in data science

Conclusion

Links:
LinkedIn: https://www.linkedin.com/in/supreet-kaur1995/

Databuzz page: https://www.linkedin.com/company/databuzz-club/

Medium Blog Page: https://medium.com/@supreetkaur_66831

ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
54 min
September 30, 2022Building Data Science Practice - Andrey Shtylenko
We talked about:
Audience Poll

Andrey’s background

What data science practice is

Best DS practice in a traditional company vs IT-centric companies

Getting started with building data science practice (finding out who you report to)

Who the initiative comes from

Finding out what kind of problems you will be solving (Centralized approach)

Moving to a semi-decentralized approach

Resources to learn about data science practice

Pivoting from the role of a software engineer to data scientist

The most impactful realization from data science practice

Advice for individual growth

Finding Andrey online
Links:
Data Teams book: https://www.amazon.com/Data-Teams-Management-Successful-Data-Focused/dp/1484262271/

ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
50 min
September 23, 2022 No episode this week
Have a great weekend!
1 min
September 16, 2022Leading Data Research - David Bader
We talked about:
David’s background

A day in the life of a professor

David’s current projects

Starting a school

The different types of professors

David’s recent papers

Similarities and differences between research labs and startups

Finding (or creating) good datasets

David’s lab

Balancing research and teaching as a professor

David’s most rewarding research project

David’s most underrated research project

David’s virtual data science seminars on YouTube

Teaching at universities without doing research

Staying up-to-date in research

David’s favorite conferences

Selecting topics for research

Convincing students to stay in academia and competing with industry

Finding David online
Links:
David A. Bader: https://davidbader.net/

NJIT Institute for Data Science: https://datascience.njit.edu/

Arkouda: https://github.com/Bears-R-Us/arkouda

NJIT Data Science YouTube Channel: https://www.youtube.com/c/NJITInstituteforDataScience

ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
59 min
September 09, 2022Dataset Creation and Curation - Christiaan Swart
We talked about:
Christiaan’s background

Usual ways of collecting and curating data

Getting the buy-in from experts and executives

Starting an annotation booklet

Pre-labeling

Dataset collection

Human level baseline and feedback

Using the annotation booklet to boost annotation productivity

Putting yourself in the shoes of annotators (and measuring performance)

Active learning

Distance supervision

Weak labeling

Dataset collection in career positioning and project portfolios

IPython widgets

GDPR compliance and non-English NLP

Finding Christiaan online

Links:
My personal blog: https://useml.net/

Comtura, my company: https://comtura.ai/

LI: https://www.linkedin.com/in/christiaan-swart-51a68967/

Twitter: https://twitter.com/swartchris8/

ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
57 min
September 02, 2022Data Mesh 101 - Zhamak Dehghani
We talked about:
Zhamak’s background

What is Data Mesh?

Domain ownership

Determining what to optimize for with Data Mesh

Decentralization

Data as a product

Self-serve data platforms

Data governance

Understanding Data Mesh

Adopting Data Mesh

Resources on implementing Data Mesh

Links:
Free 30-day code from O'Reilly: https://learning.oreilly.com/get-learning/?code=DATATALKS22

Data Mesh book: https://learning.oreilly.com/library/view/data-mesh/9781492092384/

LinkedIn: https://www.linkedin.com/in/zhamak-dehghani

ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
55 min
August 26, 2022Growing Data Engineering Team in a Scale-Up - Mehdi OUAZZA
We talked about:
Mehdi’s background

The difference between startup, scale-up and enterprise

Hypergrowth

Data platform engineers in a scale-up environment

What a data platform is and who builds it

Managing the fast pace of a scale-up while ensuring personal growth

Should a senior data person consider a scale-up or an enterprise?

Should a junior data person consider a scale-up or an enterprise?

Sourcing talent for hyper-growth companies and developing a community culture

Generating content and getting feedback

Generalization vs specialization for data engineers in a scale-up

The ratio of work between platform building and use case pipelines

Being proactive in order to progress to mid or senior level

Caps and bass guitars

MehdiO DataTV and DataCreators.Club (Mehdi’s YouTube Channel and podcast)

Links:
Mehdi's YouTube channel: https://www.youtube.com/channel/UCiZxJB0xWfPBE2omVZeWPpQ

Mehdi's Linkedin: https://linkedin.com/in/mehd-io/

Mehdi's Medium Blog: https://medium.com/@mehdio

Mehdi's data creators club: https://datacreators.club/

ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
54 min