DataTalks.Club

By DataTalks.Club

DataTalks.Club - the place to talk about data!... more

· Technology

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FAQs about DataTalks.Club:

How many episodes does DataTalks.Club have?

The podcast currently has 185 episodes available.

DataTalks.Club episodes:

August 06, 2021Approach Learning as ML Project - Vladimir Finkelshtein [mini]
We don't have an episode lined up for this week, but we recorded a small chat with Vladimir some time ago. Enjoy it!
We talked about:
Vladimir's background

Learning by answering questions

Don't be afraid of being wrong

Winnings books

Learning random things

Approach learning as a machine learning project

Links:
Vladimir on LinkedIn: https://www.linkedin.com/in/vladimir-finkelshtein/

Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
...more
14min
July 30, 2021Humans in the Loop - Lina Weichbrodt
We talked about:
Lina’s background

What we need to remember when starting a project (checklists)

Make sure the problem is formalized and close to the core business

Get the buy-in with stakeholders

Building trust with stakeholders

Don’t just focus on upsides – ask about concerns

Turning a concert into a metric

What happens when something goes wrong?

Post mortem reporting

Apply the 5 why’s

If a lot of users say it’s a bug – it’s worth investigating

Post mortem format

Action points

Debugging vs explaining the model

Are there online versions of checklists?

Make sure to log your inputs

Talking to end-users and using your own service

Your ideas vs Stakeholder ideas

Should data practitioners educate the team about data?

People skills and ‘dirty’ hacks

Where to find Lina

Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
...more
58min
July 23, 2021Running from Complexity - Ben Wilson
We talked about:
Ben’s Background

Building solutions for customers

Why projects don’t make it to production

Why do people choose overcomplicated solutions?

The dangers of isolating data science from the business unit

The importance of being able to explain things

Maximizing chances of making into production

The IKEA effect

Risks of implementing novel algorithms

If it can be done simply – do that first

Don’t become the guinea pig for someone’s white paper

The importance of stat skills and coding skills

Structuring an agile team for ML work

Timeboxing research

Mentoring

Ben’s book

‘Uncool techniques’ at AI-First companies

Should managers learn data science?

Do data scientists need to specialize to be successful?

Links:
Ben's book: https://www.manning.com/books/machine-learning-engineering-in-action (get 35% off with code "ctwsummer21")

Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
...more
1h 12min
July 16, 2021I Want to Build a Machine Learning Startup! - Elena Samuylova
We talked about:
Elena’s background

Why do a startup instead of being an employee?

Where to get ideas for your startup

Finding a co-founder

What should you consider before starting a startup?

Vertical startup vs infrastructure startup

‘AI First’ startups

Building tools for engineers

What skills do you need to start a startup?

Startup risks

How to be prepared to fail

Work-life balance

The part-time startup approach

Startup investment models

No resources and no technical expertise – what to do?

Productionizing your services

When to hire an expert

Talking to people with a problem before solving the problem

Starting Elena’s startup, Evidently

Elena’s role at Evidently

Why is Evidently open source?

“People will just copy my open source code. Should I be concerned?”

Bottom-up adoption

Creating value so that clients engage with your product

Is there a difference between countries when creating a startup?

Does open source mean the data is safer?

When should you hire engineers?

Following the market

Startups out of genuine interest vs Just for money and for fun

Links:
EvidentlyAI: https://evidentlyai.com/

Elena's LinkedIn: https://www.linkedin.com/in/elenasamuylova/

Elena's Twitter: https://twitter.com/elenasamuylova/

Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
...more
59min
July 09, 2021Big Data Engineer vs Data Scientist - Roksolana Diachuk
Links:
Twitter: https://twitter.com/dead_flowers22

LinkedIn: https://www.linkedin.com/in/roksolanadiachuk/

Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
...more
1h 2min
July 02, 2021Build Your Own Data Pipeline - Andreas Kretz
We talked about:
Andreas’s background

Why data engineering is becoming more popular

Who to hire first – a data engineer or a data scientist?

How can I, as a data scientist, learn to build pipelines?

Don’t use too many tools

What is a data pipeline and why do we need it?

What is ingestion?

Can just one person build a data pipeline?

Approaches to building data pipelines for data scientists

Processing frameworks

Common setup for data pipelines — car price prediction

Productionizing the model with the help of a data pipeline

Scheduling

Orchestration

Start simple

Learning DevOps to implement data pipelines

How to choose the right tool

Are Hadoop, Docker, Cloud necessary for a first job/internship?

Is Hadoop still relevant or necessary?

Data engineering academy

How to pick up Cloud skills

Avoid huge datasets when learning

Convincing your employer to do data science

How to find Andreas

Links:
LinkedIn: https://www.linkedin.com/in/andreas-kretz

Data engieering cookbook: https://cookbook.learndataengineering.com/

Course: https://learndataengineering.com/

Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
...more
1h 2min
June 25, 2021From Software Engineering to Machine Learning - Santiago Valdarrama
We talked about:
Santiago’s background

“Transitioning to ML” vs “Adding ML as a skill”

Getting over the fear of math for software developers

Learning by explaining

Seven lessons I learned about starting a career in machine learning

Lesson 1 – Take the first step

Lesson 2 – Learning is a marathon, not a sprint

Lesson 3 – If you want to go quickly, go alone. If you want to go far, go together.

Lesson 4 – Do something with the knowledge you gain

Lesson 5 – ML is not just math. Math is not scary.

Lesson 6 – Your ability to analyze a problem is the most important skill. Coding is secondary.

Lesson 7 – You don’t need to know every detail

Tools and frameworks needed to transition to machine learning

Problem-based learning vs Top-down learning

Learning resources

Santiago’s favorite books

Santiago’s course on transitioning to machine learning

Improving coding skills

Building solutions without machine learning

Becoming a better engineer

What is the difference between machine learning and data science?

Getting into machine learning - Reiteration

Getting past the math

Links:
Santiago's Twitter: https://twitter.com/svpino

Santiago's course: https://gumroad.com/svpino#kBjbC

Pinned tweet with a roadmap: https://twitter.com/svpino/status/1400798154732212230

Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
...more
1h
June 18, 2021Analytics Engineer: New Role in a Data Team - Victoria Perez Mola
Links:
https://www.notion.so/Analytics-Engineer-New-Role-in-a-Data-Team-9decbf33825c4580967cf3173eb77177

https://www.linkedin.com/in/victoriaperezmola/

Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
Conference: https://datatalks.club/conferences/2021-summer-marathon.html
...more
1h
June 11, 2021Data Governance - Jessi Ashdown, Uri Gilad
We talked about:
Jessi’s background

Uri’s background

Data governance

Implementing data governance: policies and processes

Reasons not to have data governance

Start with “why”

Cataloging and classifying our data

Let data work for you

The human component

Data quality

Defining policies

Implementing policies

Shopping-card experience for requesting data

Proving the value of data catalog

Using data catalog

Data governance = data catalog?

Links:
Book: https://www.oreilly.com/library/view/data-governance-the/9781492063483/

Jessi’s LinkedIn: https://www.linkedin.com/in/jashdown/

Uri’s LinkedIn: https://linkedin.com/in/ugilad

Uri’s Twitter: https://twitter.com/ugilad

Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
Conference: https://datatalks.club/conferences/2021-summer-marathon.html
...more
58min
June 04, 2021What Data Scientists Don’t Mention in Their LinkedIn Profiles - Yury Kashnitsky
We talked about:
Yury’s background

Failing fast: Grammarly for science

Not failing fast: Keyword recommender

Four steps to epiphany

Lesson learned when bringing XGBoost into production

When data scientists try to be engineers

Joining a fintech startup: Doing NLP with thousands of GPUs

Working at a Telco company

Having too much freedom

The importance of digital presence

Work-life balance

Quantifying impact of failing projects on our CVs

Business trips to Perm: don’t work on the weekend

What doesn’t kill you makes you stronger

Links:
Yury's course: https://mlcourse.ai/

Yury's Twitter: https://twitter.com/ykashnitsky

Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
...more
1h

FAQs about DataTalks.Club:

How many episodes does DataTalks.Club have?

The podcast currently has 185 episodes available.

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