DataTalks.Club

By DataTalks.ClubTechnology

DataTalks.Club episodes

March 24, 2023SE4ML - Software Engineering for Machine Learning - Nadia Nahar
We talked about:
Nadia’s background

Academic research in software engineering

Design patterns

Software engineering for ML systems

Problems that people in industry have with software engineering and ML

Communication issues and setting requirements

Artifact research in open source products

Product vs model

Nadia’s open source product dataset

Failure points in machine learning projects

Finding solutions to issues using Nadia’s dataset and experience

The problem of siloing data scientists and other structure issues

The importance of documentation and checklists

Responsible AI

How data scientists and software engineers can work in an Agile way

Links:
Model Card: https://arxiv.org/abs/1810.03993

Datasheets: https://arxiv.org/abs/1803.09010

Factsheets: https://arxiv.org/abs/1808.07261

Research Paper: https://www.cs.cmu.edu/~ckaestne/pdf/icse22_seai.pdf

Arxiv version: https://arxiv.org/pdf/2110.

Free data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
54 min
March 17, 2023Starting a Consultancy in the Data Space - Aleksander Kruszelnicki
We talked about:
Aleksander’s background

The difficulty of selling data stack as a service

How Aleksander got into consulting

The Mom Test – extracting feedback from people

User interviews

Why Aleksander’s data stack as a service startup was not viable

How Aleksander decided to switch to consulting

Finding clients to consult

Figuring out how to position your services

Geographical limitations

Figuring out your target audience

The importance of networking and marketing

Pricing your services

The pitfalls of daily and hourly pricing and how to balance incentives

Is Germany a good place to found a company?

Aleksander’s book recommendations

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

Twitter: https://twitter.com/alkrusz

Website: www.leukos.io

Free data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
53 min
March 10, 2023Biohacking for Data Scientists and ML Engineers - Ruslan Shchuchkin
We talked about:
Ruslan’s background

Fighting procrastination and perfectionism

What is biohacking?

The role of dopamine and other hormones in daily life

How meditation can help

The influence light has on our bodies

Behavioral biohacking

Daylight lamps and using light to wake up

Sleep cycles

How nutrition affects productivity

Measuring productivity

Examples of unsuccessful biohacking attempts

Stoicism, voluntary discomfort, and self-challenges

Biohacking risks and ways to prevent them

Coffee and tea biohacking

Using self-reflection and tracking to measure results

Mindset shifting

Stoicism book recommendation

Work/life balance

Ruslan’s biohacking resource recommendation

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

ree data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
53 min
March 03, 2023Analytics for a Better World - Parvathy Krishnan
We talked about:
Parvathy’s background

Brainstorming sessions with nonprofits to establish data maturity

Example of an Analytics for a Better World project

The overall data maturity situation of nonprofits vs private sector

Solving the skill gap

Publicly available content

The Analytics for a Better World Academy

The Academy’s target audience

How researchers can work with Analytics for a Better World

Improving data maturity in nonprofit organizations

People, processes, and technology

Typical tools that Analytics for a Better World recommends to nonprofits

Profiles in nonprofits

Does Analytics for a Better World has a need for data engineers?

The Analytics for a Better World team

Factors that help organizations become more data-driven

Parvathy’s resource recommendations

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

Twitter: https://twitter.com/ABWInstitute

Github: https://github.com/Analytics-for-a-Better-World

Website: https://analyticsbetterworld.org/

Free data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
55 min
February 24, 2023Accelerating the Adoption of AI through Diversity - Dânia Meira
We talked about:
Dania’s background

Founding the AI Guild

Datalift Summit

Coming up with meetup topics

Diversity in Berlin

Other types of diversity besides gender

The pitfalls of lacking diversity

Creating an environment where people can safely share their experiences

How the AI Guild helps organizations become more diverse

How the AI guild finds women in the fields of AI and data science

Advice for people in underrepresented groups

Organizing a welcoming environment and creating a code of conduct

AI Guild’s consulting work and community

AI Guild team

Dania’s resource recommendations

Upcoming Datalift Summit

Links:
Call for Speakers for the #datalift summit (Berlin, 14 to 16 June 2023): https://eu1.hubs.ly/H02RXvX0

Coded Bias documentary on Netflix: https://www.netflix.com/de/title/81328723#:~:text=This%20documentary%20investigates%20the%20bias,flaws%20in%20facial%20recognition%20technology.

Book Weapons of Math Destruction by Cathy O'Neil: https://en.wikipedia.org/wiki/Weapons_of_Math_Destruction

Book Lean In by Sheryl Sandberg: https://en.wikipedia.org/wiki/Lean_In

Free data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
57 min
February 17, 2023Staff AI Engineer - Tatiana Gabruseva
We talked about:
Tatiana’s background

Going from academia to healthcare to the tech industry

What staff engineers do

Transferring skills from academia to industry and learning new ones

The importance of having mentors

Skipping junior and mid-level straight into the staff role

Convincing employers that you can take on a lead role

Seeing failure as a learning opportunity

Preparing for coding interviews

Preparing for behavioral and system design interviews

The importance of having a network and doing mock interviews

How much do staff engineers work with building pipelines, data science, ETC, MPOps, etc.?

Context switching

Advice for those going from academia to industry

The most exciting thing about working as an AI staff engineer

Tatiana’s book recommendations

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

Twitter: https://twitter.com/tatigabru

Github: https://github.com/tatigabru

Website: http://tatigabru.com/

Free data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
56 min
February 11, 2023The Journey of a Data Generalist: From Bioinformatics to Freelancing - Jekaterina Kokatjuhha
We talked about:
Jekaterina’s background

How Jekaterina started freelancing

Jekaterina’s initial ways of getting freelancing clients

How being a generalist helped Jekaterina’s career

Connecting business and data

How Jekaterina’s LinkedIn posts helped her get clients

Jekaterina’s work in fundraising

Cohorts and KPIs

Improving communication between the data and business teams

Motivating every link in the company’s chain

The cons of freelancing

Balancing projects and networking

The importance of enjoying what you do

Growing the client base

In the office work vs working remotely

Jekaterina’s advice who people who feel stuck

Jekaterina’s resource recommendations
Links:
Jekaterina's LinkedIn: https://www.linkedin.com/in/jekaterina-kokatjuhha/
Join DataTalks.Club: https://datatalks.club/slack.html
53 min
February 03, 2023Navigating Career Changes in Machine Learning - Chris Szafranek
We talked about
Chris’s background

Switching careers multiple times

Freedom at companies

Chris’s role as an internal consultant

Chris’s sabbatical

ChatGPT

How being a generalist helped Chris in his career

The cons of being a generalist and the importance of T-shaped expertise

The importance of learning things you’re interested in

Tips to enjoy learning new things

Recruiting generalists

The job market for generalists vs for specialists

Narrowing down your interests

Chris’s book recommendations

Links:
Lex Fridman: science, philosophy, media, AI (especially earlier episodes): https://www.youtube.com/lexfridman

Andrej Karpathy, former Senior Director of AI at Tesla, who's now focused on teaching and sharing his knowledge: https://www.youtube.com/@AndrejKarpathy

Beautifully done videos on engineering of things in the real world: https://www.youtube.com/@RealEngineering

Chris' website: https://szafranek.net/

Zalando Tech Radar: https://opensource.zalando.com/tech-radar/

Modal Labs, new way of deploying code to the cloud, also useful for testing ML code on GPUs: https://modal.com

Excellent Twitter account to follow to learn more about prompt engineering for ChatGPT: https://twitter.com/goodside

Image prompts for Midjourney: https://twitter.com/GuyP

Machine Learning Workflows in Production - Krzysztof Szafanek: https://www.youtube.com/watch?v=CO4Gqd95j6k

From Data Science to DataOps: https://datatalks.club/podcast/s11e03-from-data-science-to-dataops.html

Free data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
56 min
January 27, 2023Preparing for a Data Science Interview - Luke Whipps
We talked about:
Luke’s background

Luke’s podcast - AI Game Changers

How Luke helps people get jobs

What’s changed in the recruitment market over the last 6 months

Getting ready for the interview process

Stage “zero” – the filter between the candidate and the company

Preparing for the introduction stage – research and communication

Reviewing the fundamentals during preparation

Preparing for the technical part of the interview

Establishing the hiring company’s expectations

Depth vs breadth

Overly theoretical and mathematical questions in interviews

Bombing (failing) in the middle of an interview

Applying to different roles within the same company

Luke’s resource recommendations

Links:
Luke's LinkedIn: https://www.linkedin.com/in/lukewhipps/

Free data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
55 min
January 20, 2023Indie Hacking - Pauline Clavelloux
We talked about:
Pauline’s background

Pauline’s work as a manager at IBM

What is indie hacking?

Pauline initial indie hacking projects

Getting ready for launch

Responsibilities and challenges in indie hacking

Pauline’s latest indie hacking project

Going live and marketing

Challenges with Unreal Me

Staying motivated with indie hacking projects

Skills Pauline picked up while doing indie hacking projects

Balancing a day job and indie hacking

Micro SaaS and AboutStartup.io

How Pauline comes up with ideas for projects

Going from an idea on paper to building a project

Pauline’s Twitter success

Connecting with Pauline online

Pauline’s indie hacking inspiration

Pauline’s resource recommendation

Links:
Website: https://wintopy.io/

Pauline's Twitter: https://twitter.com/Pauline_Cx

Pauline's LinkedIn: https://www.linkedin.com/in/paulineclavelloux/

Blog about Indiehacking: https://aboutstartup.io

Free data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
52 min