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Data Science at Home
https://datascienceat...
Belgium

Technology, machine learning and algorithms

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Fighting Climate Change as a Technologist (Ep. 172)
Durée : 19min 3s
AI in the Enterprise with IBM Global AI Strategist Mara Pometti (Ep. 171)
Durée : 35min 2s
Speaking about data with Mikkel Settnes from Dreamdata.io (Ep. 170)
Durée : 34min 28s
Send compute to data with POSH data-aware shell (Ep. 169)
Durée : 22min 8s
How are organisations doing with data and AI? (Ep. 168)
Durée : 35min 34s
Don't fight! Cooperate. Generative Teaching Networks (Ep. 167)
Durée : 16min 3s
CSV sucks. Here is why. (Ep. 166)
Durée : 20min 6s
Reinforcement Learning is all you need. Or is it? (Ep. 165)
Durée : 30min 28s
What's happening with AI today? (Ep. 164)
Durée : 25min 6s
2 effective ways to explain your predictions (Ep. 163)
Durée : 24min 19s
The Netflix challenge. Fair or what? (Ep. 162)
Durée : 21min 55s
Artificial Intelligence for Blockchains with Jonathan Ward CTO of Fetch AI (Ep. 161)
Durée : 32min 38s
Apache Arrow, Ballista and Big Data in Rust with Andy Grove RB (Ep. 160)
Durée : 29min 0s
GitHub Copilot: yay or nay? (Ep. 159)
Durée : 32min 22s
Pandas vs Rust [RB] (Ep. 158)
Durée : 31min 34s
A simple trick for very unbalanced data (Ep. 157)
Durée : 22min 1s
Time to take your data back with Tapmydata (Ep. 156)
Durée : 41min 21s
True Machine Intelligence just like the human brain (Ep. 155)
Durée : 33min 36s
Delivering unstoppable data with Streamr (Ep. 154)
Durée : 42min 59s
MLOps: the good, the bad and the ugly (Ep. 153)
Durée : 24min 41s
MLOps: what is and why it is important Part 2 (Ep. 152)
Durée : 30min 36s
MLOps: what is and why it is important (Ep. 151)
Durée : 33min 4s
Can I get paid for my data? With Mike Andi from Mytiki (Ep. 150)
Durée : 39min 3s
Building high-growth data businesses with Lillian Pierson (Ep. 149)
Durée : 25min 33s
Learning and training in AI times (Ep. 148)
Durée : 31min 53s
You are the product [RB] (Ep. 147)
Durée : 45min 4s
Polars: the fastest dataframe crate in Rust - with Ritchie Vink (Ep. 146)
Durée : 32min 52s
Apache Arrow, Ballista and Big Data in Rust with Andy Grove (Ep. 145)
Durée : 30min 15s
Pandas vs Rust (Ep. 144)
Durée : 31min 40s
Concurrent is not parallel - Part 2 (Ep. 143)
Durée : 15min 21s
Concurrent is not parallel - Part 1 (Ep. 142)
Durée : 32min 10s
Backend technologies for machine learning in production (Ep. 141)
Durée : 25min 11s
How to reinvent banking and finance with data and technology (Ep. 139)
Durée : 36min 47s
What's up with WhatsApp? (Ep. 138)
Durée : 30min 44s
Is Rust flexible enough for a flexible data model? (Ep. 137)
Durée : 28min 37s
Is Apple M1 good for machine learning? (Ep.136)
Durée : 28min 21s
Rust and deep learning with Daniel McKenna (Ep. 135)
Durée : 22min 59s
Scaling machine learning with clusters and GPUs (Ep. 134)
Durée : 30min 58s
What is data ethics? (Ep. 133)
Durée : 25min 36s
A Standard for the Python Array API (Ep. 132)
Durée : 33min 40s
What happens to data transfer after Schrems II? (Ep. 131)
Durée : 31min 54s
Test-First Machine Learning [RB] (Ep. 130)
Durée : 20min 51s
Similarity in Machine Learning (Ep. 129)
Durée : 30min 19s
Distill data and train faster, better, cheaper (Ep. 128)
Durée : 23min 46s
Machine Learning in Rust: Amadeus with Alec Mocatta [RB] (ep. 127)
Durée : 24min 19s
Top-3 ways to put machine learning models into production (Ep. 126)
Durée : 20min 27s
Remove noise from data with deep learning (Ep.125)
Durée : 23min 59s
What is contrastive learning and why it is so powerful? (Ep. 124)
Durée : 26min 12s
Neural search (Ep. 123)
Durée : 19min 18s
Let's talk about federated learning (Ep. 122)
Durée : 30min 10s
How to test machine learning in production (Ep. 121)
Durée : 28min 48s
Why synthetic data cannot boost machine learning (Ep. 120)
Durée : 23min 23s
Machine learning in production: best practices [LIVE from twitch.tv] (Ep. 119)
Durée : 37min 31s
Testing in machine learning: checking deeplearning models (Ep. 118)
Durée : 18min 17s
Testing in machine learning: generating tests and data (Ep. 117)
Durée : 20min 18s
Why you care about homomorphic encryption (Ep. 116)
Durée : 18min 50s
Test-First machine learning (Ep. 115)
Durée : 19min 44s
GPT-3 cannot code (and never will) (Ep. 114)
Durée : 19min 6s
Make Stochastic Gradient Descent Fast Again (Ep. 113)
Durée : 20min 35s
What data transformation library should I use? Pandas vs Dask vs Ray vs Modin vs Rapids (Ep. 112)
Durée : 21min 10s
[RB] It’s cold outside. Let’s speak about AI winter (Ep. 111)
Durée : 36min 54s
Rust and machine learning #4: practical tools (Ep. 110)
Durée : 24min 18s
Rust and machine learning #3 with Alec Mocatta (Ep. 109)
Durée : 23min 58s
Rust and machine learning #2 with Luca Palmieri (Ep. 108)
Durée : 27min 2s
Rust and machine learning #1 (Ep. 107)
Durée : 22min 27s
Protecting workers with artificial intelligence (with Sandeep Pandya CEO Everguard.ai)(Ep. 106)
Durée : 16min 20s
Compressing deep learning models: rewinding (Ep.105)
Durée : 15min 31s
Compressing deep learning models: distillation (Ep.104)
Durée : 22min 19s
Pandemics and the risks of collecting data (Ep. 103)
Durée : 20min 9s
Why average can get your predictions very wrong (ep. 102)
Durée : 14min 47s
Activate deep learning neurons faster with Dynamic RELU (ep. 101)
Durée : 22min 18s
WARNING!! Neural networks can memorize secrets (ep. 100)
Durée : 24min 16s
Attacks to machine learning model: inferring ownership of training data (Ep. 99)
Durée : 19min 39s
Don't be naive with data anonymization (Ep. 98)
Durée : 13min 41s
Why sharing real data is dangerous (Ep. 97)
Durée : 10min 35s
Building reproducible machine learning in production (Ep. 96)
Durée : 14min 20s
Bridging the gap between data science and data engineering: metrics (Ep. 95)
Durée : 13min 25s
A big welcome to Pryml: faster machine learning applications to production (Ep. 94)
Durée : 9min 26s
It's cold outside. Let's speak about AI winter (Ep. 93)
Durée : 36min 48s
The dark side of AI: bias in the machine (Ep. 92)
Durée : 20min 26s
The dark side of AI: metadata and the death of privacy (Ep. 91)
Durée : 23min 0s
The dark side of AI: recommend and manipulate (Ep. 90)
Durée : 20min 33s
The dark side of AI: social media and the optimization of addiction (Ep. 89)
Durée : 22min 45s
More powerful deep learning with transformers (Ep. 84) (Rebroadcast)
Durée : 37min 44s
How to improve the stability of training a GAN (Ep. 88)
Durée : 28min 16s
How to improve the stability of training a GAN (Ep. 88)
Durée : 28min 20s
What if I train a neural network with random data? (with Stanisław Jastrzębski) (Ep. 87)
Durée : 19min 37s
Deeplearning is easier when it is illustrated (with Jon Krohn) (Ep. 86)
Durée : 44min 53s
[RB] How to generate very large images with GANs (Ep. 85)
Durée : 14min 41s
[RB] Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan) (Ep. 83)
Durée : 37min 47s
What is wrong with reinforcement learning? (Ep. 82)
Durée : 21min 48s
Have you met Shannon? Conversation with Jimmy Soni and Rob Goodman about one of the greatest minds …
Durée : 32min 21s
Attacking machine learning for fun and profit (with the authors of SecML Ep. 80)
Durée : 34min 4s
[RB] How to scale AI in your organisation (Ep. 79)
Durée : 13min 21s
Training neural networks faster without GPU [RB] (Ep. 77)
Durée : 22min 21s
[RB] Complex video analysis made easy with Videoflow (Ep. 75)
Durée : 30min 42s
[RB] Validate neural networks without data with Dr. Charles Martin (Ep. 74)
Durée : 44min 46s
How to cluster tabular data with Markov Clustering (Ep. 73)
Durée : 20min 43s
Waterfall or Agile? The best methodology for AI and machine learning (Ep. 72)
Durée : 14min 26s
Episode 68: AI and the future of banking with Chris Skinner [RB]
Durée : 41min 42s

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