Andrew Fairless, Ph.D.
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2021-05-21
What I Read: Bayesian and frequentist results
2021-05-20
What I Read: Clustergam
2021-05-19
What I Watch: Visualising software architecture, C4 model
2021-05-18
What I Read: Adversarial Neural Cryptography
2021-05-17
What I Watch: When To Use Microservices
2021-05-14
What I Read: AI, Colon Cancer
2021-05-13
What I Read: 3 Statistical Paradoxes
2021-05-12
What I Read: Continuous Training Strategy
2021-05-11
What I Read: Models of Data Science teams
2021-05-10
What I Read: Reducing Toxicity in Language Models
2021-05-07
What I Read: Decentralized AI For Healthcare
2021-05-06
What I Read: Zero-Shot Learning
2021-05-05
What I Read: Weight Banding
2021-05-04
What I Read: Branch Specialization
2021-05-03
What I Read: Visualizing Weights
2021-04-29
What I Read: Understanding Key-Value Databases
2021-04-28
What I Read: Why machine learning struggles with causality
2021-04-27
What I Read: Object-Oriented Programming Disaster
2021-04-26
What I Read: Computer Scientist Who Tackles Inequality
2021-04-25
What I Read: Ezra Klein Interviews Alison Gopnik
2021-04-24
What I Read: Deep Learning Recommendation Models
2021-04-22
What I Read: What did COVID do to models?
2021-04-21
What I Read: Compare ML Experiment Tracking Tools
2021-04-20
What I Read: AutoML, Multi-task learning, Multi-tower models, Ads
2021-04-19
What I Read: Scaling vs. Normalizing Data
2021-04-18
What I Read: Brain ‘Rotates’ Memories to Save Them From New Sensations
2021-04-17
What I Read: Rip van Winkles Razor, Adaptive Data Analysis
2021-04-15
What I Read: Unit testing best practices
2021-04-14
What I Read: Common Errors when Debugging Airflow DAGs
2021-04-13
What I Read: Software Engineering Best Practices for Data Scientists
2021-04-12
What I Read: My Love / Hate Relationship With Jupyter
2021-04-10
What I Read: Deep learning model compression
2021-04-09
What I Read: New Algorithm, Linear Equations
2021-04-06
What I Read: Statistics, Geometry Problem
2021-04-05
What I Watch: Regaining Control in Deep Systems
2021-04-04
What I Read: Exploiting machine learning pickle files
2021-04-03
What I Watch: How to Debug Your Team
2021-04-02
What I Read: Bayesian Hierarchical Modelling at Scale
2021-04-01
What I Read: Causal design patterns
2021-03-31
What I Read: Generalization in Deep Learning
2021-03-30
What I Read: Kedro Pipelines with Airflow
2021-03-29
What I Read: Reducing High Cost of Training NLP Models
2021-03-28
What I Read: 15 common coding mistakes data scientist make
2021-03-27
What I Read: Difficulty of Graph Anonymisation
2021-03-26
What I Read: Language Model Fine-tuning
2021-03-25
What I Read: Python Concurrency
2021-03-24
What I Read: Data Quality Management
2021-03-23
What I Read: Neural Nets, How Brains Learn
2021-03-22
What I Read: Continual Learning, Amnesia, Neural Networks
2021-03-21
What I Read: Deep learning, black box
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