DataTalks.Club

By DataTalks.ClubTechnology

DataTalks.Club episodes

August 19, 2022Lessons Learned About Data & AI at Enterprises - Alexander Hendorf
We talked about:
Alexander’s background

The role of Partner at Königsweg

Being part of the data and AI community

How Alexander became chair at PyData

Alexander’s many talks and advice on giving them

Explaining AI to managers

Why being able to explain machine learning to managers is important

The experimentational nature of AI and why it’s not a cure-all

Innovation requires patience

Convincing managers not to use AI or ML when there are better (simpler) solutions

The role of MLOps in enterprises

Thinking about the mid- and long-term when considering solutions

Finding Alexander online

Links:
Alexander's Twitter: https://twitter.com/hendorf

Alexander's LinkedIn: https://www.linkedin.com/in/hendorf/

Königsweg: https://www.koenigsweg.com

PyData Südwest: https://www.meetup.com/pydata-suedwest/

PyData Frankfurt: https://www.meetup.com/pydata-frankfurt/

PyConDE & PyData Berlin: https://pycon.de

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 12, 2022MLOps Architect - Danny Leybzon
We talked about:
Danny’s background

What an MLOps Architect does

The popularity of MLOps Architect as a role

Convincing an employer that you can wear many different hats

Interviewing for the role of an MLOps Architect

How Danny prioritizes work with data scientists

Coming to WhyLabs when you’ve already got something in production vs nothing in production

Market awareness regarding the importance of model monitoring

How Danny (WhyLabs) chooses tools

ONNX

Common trends in tooling setups

The most rewarding thing for Danny in ML and data science

Danny’s secret for staying sane while wearing so many different hats

T-shaped specialist, E-shaped specialist, and the horizontal line

The importance of background for the role of an MLOps Architect

Key differences for WhyLogs free vs paid

Conclusion and where to find Danny online

Links:
Matt Turck: https://mattturck.com/data2021/

AI Observability Platform: https://whylabs.ai/observability

Danny's LinkedIn: https://www.linkedin.com/in/dleybz/

Whylabs' website: https://whylabs.ai/

AI Infrastructure Alliance: https://ai-infrastructure.org/

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
August 05, 2022Decoding Data Science Job Descriptions - Tereza Iofciu
We talked about:
DataTalks.Club intro

Tereza’s background

Working as a coach

Identifying the mismatches between your needs and that of a company

How to avoid misalignments

Considering what’s mentioned in the job description, what isn’t, and why

Diversity and culture of a company

Lack of a salary in the job description

Way of doing research about the company where you will potentially work

How to avoid a mismatch with a company other than learning from your mistakes

Before data, during data, after data (a company’s data maturity level)

The company’s tech stack

Finding Tereza online

Links:
Decoding Data Science Job Descriptions (talk): https://www.youtube.com/watch?v=WAs9vSNTza8

Talk at ConnectForward: https://www.youtube.com/watch?v=WAs9vSNTza8

Slides: https://www.slideshare.net/terezaif/decoding-data-science-job-descriptions-250687704

Talk at DataLift: https://www.youtube.com/watch?v=pCtQ0szJiLA

Slides: https://www.slideshare.net/terezaif/lessons-learned-from-hiring-and-retaining-data-practitioners

MLOps Zoomcamp: https://github.com/DataTalksClub/mlops-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
50 min
July 29, 2022Data Science for Social Impact - Christine Cepelak
We talked about:
Christine’s Background

Private sector vs Public sector

Public policy

The challenges of being a community organizer

How public policy relates to political science

Programs that teach data science for public policy

Data science for public policy vs regular data science

The importance of ethical data science in public policy

How data science in social impact project differs from other projects

Other resources to learn about data science for public policy

Challenges with getting data in data science for public policy

The problems with accessing public datasets about recycling

Christine’s potential projects after Master’s degree

Gender inequality in STEM fields

Corporate responsibility and why organizations need social impact data scientists

What you need to start making a social impact with data science

80,000 hours

Other use cases for public policy data science

Coffee, Ethics & AI

Finding Christine online

Links:
Explore some Data Science for Social Good projects: http://www.dssgfellowship.org/projects/

Bi-weekly Ethics in AI Coffee Chat: https://www.meetup.com/coffee-ethics-ai/

Make a Social Impact with your Job: https://tinyurl.com/80khours

Course in Data Ethics: https://ethics.fast.ai/

Data Science for Social Good Berlin: https://dssg-berlin.org/

CorrelAid: https://correlaid.org/

DataKind: https://www.datakind.org/

Christine's LinkedIn: https://www.linkedin.com/in/christinecepelak/

Christine's Twitter: https://twitter.com/CLcep

MLOps Zoomcamp: https://github.com/DataTalksClub/mlops-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
49 min
July 22, 2022Hiring Data Science Talent - Olga Ivina
We talked about:
Olga’s career journey

Hiring data scientists now vs 7 years ago

The two qualities of an excellent data scientist

What makes Alexey do this podcast

How Alexey get the latest information on data science

How Olga checks a candidate’s technical skills

How to make an answer stand out (showing your depth of knowledge)

A strong mathematical background vs a strong engineering background

When Auto ML will replace the need to have data scientists

Should data scientists transition into management? (the importance of communication in an organization)

Switching from a data analyst role to a data scientist

Attracting female talent in data science

Changing a job description to find talent

Long gaps in the CV

Eierlegende Wollmilchsau

Links:
Olga's LinkedIn: https://www.linkedin.com/in/olgaivina/

Olga's Twitter: https://twitter.com/olgaivina

MLOps Zoomcamp: https://github.com/DataTalksClub/mlops-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
53 min
July 15, 2022From Open-Source Maintainer to Founder - Will McGugan
We talked about:
Will’s background

Will’s open source projects

S3Fs and PyFile systems

Inspiration for open source projects

Will as a freelancer

Starting a company from a tweet (Rich and Textual)

Building in public (Will’s approach to social media)

The workforce and roadmap of Textualize.io

The importance of working on open source for Textualize employees

The workflow of and contributions to Textualize

Getting your first thousand GitHub Stars (going viral)

Suggestions for those who wish to start in the open-source space

Finding Will online

Links:
Twitter: https://twitter.com/willmcgugan

Textualize website: https://www.textualize.io/

Textualize GitHub: https://github.com/textualize

MLOps Zoomcamp: https://github.com/DataTalksClub/mlops-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
50 min
July 08, 2022Designing a Data Science Organization - Lisa Cohen
We talked about:
Lisa’s background

Centralized org vs decentralized org

Hybrid org (centralized/decentralized)

Reporting your results in a data organization

Planning in a data organization

Having all the moving parts work towards the same goals

Which approach Twitter follows (centralized vs decentralized)

Pros and cons of a decentralized approach

Pros and cons of a centralized approach

Finding a common language with all the functions of an org

Finding the right approach for companies that want to implement data science

How many data scientists does a company need?

Who do data scientists report huge findings to?

The importance of partnering closely with other functions of the org

The role of Product Managers in the org and across functions

Who does analytics at Twitter (analysts vs data scientists)

The importance of goals, objectives and key results

Conflicting objectives

The importance of research

Finding Lisa online

Links:
LinkedIn: https://www.linkedin.com/in/cohenlisa/

Twitter: https://twitter.com/lisafeig

Medium: https://medium.com/@lisa_cohen

Lisa Cohen's YouTube videos: https://www.youtube.com/playlist?list=PLRhmnnfr2bX7-GAPHzvfUeIEt2iYCbI3w

MLOps Zoomcamp: https://github.com/DataTalksClub/mlops-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
52 min
July 01, 2022Developer Advocacy Engineer for Open-Source - Merve Noyan
We talked about:
Merve’s background

Merve’s first contributions to open source

What Merve currently does at Hugging Face (Hub, Spaces)

What is means to be a developer advocacy engineer at Hugging Face

The best way to get open source experience (Google Summer of Code, Hacktoberfest, and sprints)

The peculiarities of hiring as it relates to code contributions

Best resources to learn about NLP besides Hugging Face

Good first projects for NLP

The most important topics in NLP right now

NLP ML Engineer vs NLP Data Scientist

Project recommendations and other advice to catch the eye of recruiters

Merve on Twitch and her podcast

Finding Merve online

Merve and Mario Kart

Links:
Hugging Face Course: https://hf.co/course

Natural Language Processing in TensorFlow: https://www.coursera.org/learn/natural-language-processing-tensorflow

Github ML Poetry: https://github.com/merveenoyan/ML-poetry

Tackling multiple tasks with a single visual language model: https://www.deepmind.com/blog/tackling-multiple-tasks-with-a-single-visual-language-model

Hugging Face big science/TOpp: https://huggingface.co/bigscience/T0pp

Pathways Language Model (PaLM) blog: https://ai.googleblog.com/2022/04/pathways-language-model-palm-scaling-to.html

MLOps Zoomcamp: https://github.com/DataTalksClub/mlops-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
51 min
June 24, 2022Data Scientists at Work - Mısra Turp
We talked about:
Misra’s background

What data scientists do

Consultant data scientists vs in-house data scientists (and freelancers)

Expectations for data scientists

The importance of keeping up to date with AI developments (FOMA)

How does DALL·E 2 work and should you care?

Going to conferences to stay up to date

The most pressing issue for data scientists

Fighting FOMA and imposter syndrome

Knowing when you have enough knowledge of a framework

The “best” type of data scientist

Being a generalist vs a specialist

Advice for entry-level data entering an oversaturated market

Catching the eye of big AI companies

Choosing a project for your portfolio

The importance of having a Ph.D. or Master’s degree in data science

Finding Misra online

Links:
Mısra's YouTube channel: https://www.youtube.com/channel/UCpNUYWW0kiqyh0j5Qy3aU7w

Twitter: https://twitter.com/misraturp

Hands-on Data Science: Complete Your First Portfolio Project: https://www.soyouwanttobeadatascientist.com/hods

MLOps Zoomcamp: https://github.com/DataTalksClub/mlops-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.htm
59 min
June 17, 2022Freelancing and Consulting with Data Engineering - Adrian Brudaru
We talked about:
Adrian’s background

Freelancing vs Employment

Risk and occupancy rate in freelancing

The scariest part of freelancing

Adrian’s first projects

Freelancing 5 years later

Pay rates in freelancing

Acquiring skills while freelancing

Working with recruitment agencies and networking

Looking for projects and getting clients

Freelancing vs consulting

Clarity in clients’ expectations (scope of work)

Building your network

Freelancing platforms

Adrian’s data loading prototype

Going from freelancing to making your own product (and other investments)

The usefulness of a portfolio

Introverts in freelancing

Is it possible to work for 3 months a year in freelancing?

Choosing projects and skill-building strategy (focusing on interests)

Freelancing in Berlin

Clients’ expectations for freelancers vs employees

Working with more than one client at the same time

Adrian’s freelance cooperative on Slack

Other advice for novice freelancers (networking)

Finding Adrian online

Links:
Github: https://github.com/scale-vector

Slack Community: https://join.slack.com/t/berlindatacol-szn7050/shared_invite/zt-19dp8msp0-pP4Av3_fVFBbsdrzPROEAg

MLOps Zoomcamp: https://github.com/DataTalksClub/mlops-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
53 min