Santiago Viquez
@santiviquez.com
ML @ NannyML. Writing “The Little Book of ML Metrics” https://www.nannyml.com/metrics?via=santiago
Personal website: https://www.santiviquez.com
Personal website: https://www.santiviquez.com
📕 And if you’re looking for a physical copy, grab yours here: www.nannyml.com/metrics?via=...
The Little Book of ML Metrics
The book every data scientist needs on their desk. Metrics are arguably the most important part of data science work, yet they are rarely taught in courses or university degrees. Even senior data scie...
www.nannyml.com
March 11, 2025 at 3:43 PM
📕 And if you’re looking for a physical copy, grab yours here: www.nannyml.com/metrics?via=...
Performance Estimation methods are a step forward in solving the real problem. Proud to be part of this team!
January 21, 2025 at 11:31 PM
Performance Estimation methods are a step forward in solving the real problem. Proud to be part of this team!
Big kudos to my colleagues Jakub and Wojtek for their work on this!
I’ll be honest, even at the risk of sounding biased. There are many ML monitoring companies out there, but none of them are solving the real problem. Most monitor the data, not the models.
I’ll be honest, even at the risk of sounding biased. There are many ML monitoring companies out there, but none of them are solving the real problem. Most monitor the data, not the models.
January 21, 2025 at 11:31 PM
Big kudos to my colleagues Jakub and Wojtek for their work on this!
I’ll be honest, even at the risk of sounding biased. There are many ML monitoring companies out there, but none of them are solving the real problem. Most monitor the data, not the models.
I’ll be honest, even at the risk of sounding biased. There are many ML monitoring companies out there, but none of them are solving the real problem. Most monitor the data, not the models.
Don’t overthink it. Embrace the cringe.
January 16, 2025 at 4:36 AM
Don’t overthink it. Embrace the cringe.
Ideally before the end on Q2 2025
January 9, 2025 at 2:43 AM
Ideally before the end on Q2 2025
Please recommend me your recommender system metric 😂
January 8, 2025 at 8:57 PM
Please recommend me your recommender system metric 😂
Here are the ones I have so far:
• MRR: Mean Reciprocal Rank
• ARHR@k: Average Reciprocal Hit-Rank at K
• nDCG@K: Normalized Discounted Cumulative Gain
• Precision@k
• Recall@k
• F1@K
• Average Recall@k
• Average Precision@k
• MAP: Mean Average Precision
• MRR: Mean Reciprocal Rank
• ARHR@k: Average Reciprocal Hit-Rank at K
• nDCG@K: Normalized Discounted Cumulative Gain
• Precision@k
• Recall@k
• F1@K
• Average Recall@k
• Average Precision@k
• MAP: Mean Average Precision
January 8, 2025 at 8:57 PM
Here are the ones I have so far:
• MRR: Mean Reciprocal Rank
• ARHR@k: Average Reciprocal Hit-Rank at K
• nDCG@K: Normalized Discounted Cumulative Gain
• Precision@k
• Recall@k
• F1@K
• Average Recall@k
• Average Precision@k
• MAP: Mean Average Precision
• MRR: Mean Reciprocal Rank
• ARHR@k: Average Reciprocal Hit-Rank at K
• nDCG@K: Normalized Discounted Cumulative Gain
• Precision@k
• Recall@k
• F1@K
• Average Recall@k
• Average Precision@k
• MAP: Mean Average Precision
6. "Large Language Models: A Deep Dive—Bridging Theory and Practice" (Kamath et al., 2024): amzn.to/3VZO6ct
This one is probably too long and expensive, but I want to get it haha.
Anything else to add?
This one is probably too long and expensive, but I want to get it haha.
Anything else to add?
Large Language Models: A Deep Dive: Bridging Theory and Practice
Amazon.com: Large Language Models: A Deep Dive: Bridging Theory and Practice: 9783031656460: Kamath, Uday, Keenan, Kevin, Somers, Garrett, Sorenson, Sarah: Books
amzn.to
January 2, 2025 at 2:59 PM
6. "Large Language Models: A Deep Dive—Bridging Theory and Practice" (Kamath et al., 2024): amzn.to/3VZO6ct
This one is probably too long and expensive, but I want to get it haha.
Anything else to add?
This one is probably too long and expensive, but I want to get it haha.
Anything else to add?
5. "Fundamentals of Data Engineering: Plan and Build Robust Data Systems" (Reis, Housley, 2022): amzn.to/41TJWq9
Not ML-related, but still relevant.
Fundamentals of Data Engineering: Plan and Build Robust Data Systems
Amazon.com: Fundamentals of Data Engineering: Plan and Build Robust Data Systems: 9781098108304: Reis, Joe, Housley, Matt: Books
amzn.to
January 2, 2025 at 2:59 PM
5. "Fundamentals of Data Engineering: Plan and Build Robust Data Systems" (Reis, Housley, 2022): amzn.to/41TJWq9
Not ML-related, but still relevant.