Sitemap - 2021 - Data Science at Home

It's that time of the year

History of Data Science (Ep. 181)

Capturing Data at the Edge (Ep. 180)

[RB] Composable Artificial Intelligence (Ep. 179)

What is a data mesh and why it is relevant (Ep. 178)

Environmentally friendly AI (Ep. 177)

Do you fear of AI? Why? (Ep. 176)

Composable models and artificial general intelligence (Ep. 175)

Data science gets more "human"

Ethics and explainability in AI with Erika Agostinelli from IBM (ep. 174)

Is neural hash by Apple violating our privacy? (Ep. 173)

Fighting Climate Change as a Technologist (Ep. 172)

AI in the Enterprise with IBM Global AI Strategist Mara Pometti (Ep. 171)

Speaking about data with Mikkel Settnes from Dreamdata.io (Ep. 170)

Send compute to data with POSH data-aware shell (Ep. 169)

How are organisations doing with data and AI? (Ep. 168)

Don't fight! Cooperate. Generative Teaching Networks (Ep. 167)

CSV sucks. Here is why. (Ep. 166)

Reinforcement Learning is all you need. Or is it? (Ep. 165)

What's happening with AI today? (Ep. 164)

2 effective ways to explain your predictions (Ep. 163)

The Netflix challenge. Fair or what? (Ep. 162)

Artificial Intelligence for Blockchains with Jonathan Ward CTO of Fetch AI (Ep. 161)

Apache Arrow, Ballista and Big Data in Rust with Andy Grove RB (Ep. 160)

GitHub Copilot: yay or nay? (Ep. 159)

Pandas vs Rust [RB] (Ep. 158)

A simple trick for very unbalanced data (Ep. 157)

Time to take your data back with Tapmydata (Ep. 156)

True Machine Intelligence just like the human brain (Ep. 155)

MLops is more relevant than ML

Delivering unstoppable data with Streamr (Ep. 154)

MLOps: the good, the bad and the ugly (Ep. 153)

MLOps: what is and why it is important Part 2 (Ep. 152)

MLOps: what is and why it is important (Ep. 151)

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

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

Learning and training in AI times (Ep. 148)

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

Rust is eating the world

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

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

Pandas vs Rust (Ep. 144)

Concurrent is not parallel - Part 2 (Ep. 143)

Concurrent is not parallel - Part 1 (Ep. 142)

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

You are the product (Ep. 140)

Data Science & beyond

How to reinvent banking and finance with data and technology (Ep. 139)

What's up with WhatsApp? (Ep. 138)

Is Rust flexible enough for a flexible data model? (Ep. 137)

Is Apple M1 good for machine learning? (Ep.136)

Rust and deep learning with Daniel McKenna (Ep. 135)

Welcome to the new year!