Santiago Viquez
santiviquez
AI & ML interests
ML @ NannyML.
Writing "The Little Book of ML Metrics" at https://github.com/NannyML/The-Little-Book-of-ML-Metrics
Recent Activity
Articles
Organizations
Posts
26
Post
1487
Professors should ask students to write blog posts based on their final projects instead of having them do paper-like reports.
A single blog post, accessible to the entire internet, can have a greater career impact than dozens of reports that nobody will read.
A single blog post, accessible to the entire internet, can have a greater career impact than dozens of reports that nobody will read.
Post
464
Some exciting news...
We are open-sourcing The Little Book of ML Metrics! π
The book that will be on every data scientist's desk is open source.
What does that mean?
It means hundreds of people can review it, contribute to it, and help us improve it before it's finished!
This also means that everyone will have free access to the digital version!
Meanwhile, the high-quality printed edition will be available for purchase as it has been for a while.
Revenue from printed copies will help us support further development and maintenance of the book. Not to mention that reviewers and contributors will receive revenue sharing through their affiliate links. π
Check out the book repo (make sure to leave a star π):
https://github.com/NannyML/The-Little-Book-of-ML-Metrics
We are open-sourcing The Little Book of ML Metrics! π
The book that will be on every data scientist's desk is open source.
What does that mean?
It means hundreds of people can review it, contribute to it, and help us improve it before it's finished!
This also means that everyone will have free access to the digital version!
Meanwhile, the high-quality printed edition will be available for purchase as it has been for a while.
Revenue from printed copies will help us support further development and maintenance of the book. Not to mention that reviewers and contributors will receive revenue sharing through their affiliate links. π
Check out the book repo (make sure to leave a star π):
https://github.com/NannyML/The-Little-Book-of-ML-Metrics
Collections
1
Collection of LLM hallucination and evaluation papers that I've been exploring and implementing. Some of them have my comments and annotated doodles.
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Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine Translation
Paper β’ 2208.05309 β’ Published β’ 1 -
LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language Models
Paper β’ 2305.13711 β’ Published β’ 2 -
Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation
Paper β’ 2302.09664 β’ Published β’ 3 -
BARTScore: Evaluating Generated Text as Text Generation
Paper β’ 2106.11520 β’ Published β’ 1
models
19
santiviquez/flan-t5-small-ppo
Reinforcement Learning
β’
Updated
β’
2
santiviquez/reward_modeling_anthropic_hh
Text Classification
β’
Updated
β’
7
santiviquez/quora-qa-flan-t5-small
Text2Text Generation
β’
Updated
β’
1
santiviquez/t5-small-finetuned-samsum-en
Summarization
β’
Updated
β’
35
santiviquez/bart-base-finetuned-samsum-en
Summarization
β’
Updated
β’
24
santiviquez/amazon-reviews-sentiment-bert-base-uncased-6000-samples
Updated
santiviquez/amazon-reviews-sentiment-distilbert-base-uncased-6000-samples
Text Classification
β’
Updated
β’
10
santiviquez/amazon-reviews-finetuning-distilbert-base-uncased
Text Classification
β’
Updated
β’
29
santiviquez/amazon-reviews-finetuning-distilbert-base-uncased_books
Text Classification
β’
Updated
β’
8
santiviquez/amazon-reviews-finetuning-bert-base-sentiment
Text Classification
β’
Updated
β’
12