Metrics Store in Action
With a tutorial using MetricFlow, Python, DuckDB, dbt, and Streamlit- 23176Murphy ≡ DeepGuide
A Practical Approach to Evaluating Positive-Unlabeled (PU) Classifiers in Business Analytics
An approach for evaluating PU models with common classification metrics adjusted for the prior probability of the positive class- 22611Murphy ≡ DeepGuide
How to Assess Recommender Systems
A deep dive on Evaluation Metrics Formulas- 25464Murphy ≡ DeepGuide
Beyond Accuracy: Exploring Exotic Metrics for Holistic Evaluation of Machine Learning Models
Machine learning has undoubtedly become a powerful tool in today's data-driven world, but are we truly tapping into its full potential...- 21511Murphy ≡ DeepGuide
Similarity Search, Part 7: LSH Compositions
Dive into combinations of LSH functions to guarantee a more reliable search- 20454Murphy ≡ DeepGuide
Comprehensive Guide to Ranking Evaluation Metrics
Explore an abundant choice of metrics and find the best one for your problem- 25168Murphy ≡ DeepGuide
The Guide to Recommender Metrics
Evaluating a recommender system offline can be tricky- 28162Murphy ≡ DeepGuide
XPER: Unveiling the Driving Forces of Predictive Performance
A new method for decomposing your favorite performance metrics- 22684Murphy ≡ DeepGuide
How to Perform Hallucination Detection for LLMs
Hallucination metrics for open-domain and closed-domain question answering- 20620Murphy ≡ DeepGuide
The Ultimate Guide to Making Sense of Data
Lessons from 10 years at Uber, Meta and High-Growth Startups- 29040Murphy ≡ DeepGuide
How to Design Better Metrics
9 best practices from leading companies like Uber & Meta- 26598Murphy ≡ DeepGuide
Make Metrics Matter
How data professionals can increase the impact of their strongest asset- 20304Murphy ≡ DeepGuide
Stop the Count! Why Putting A Time Limit on Metrics is Critical for Fast and Accurate Experiments
Why your experiments might never reach significance- 22304Murphy ≡ DeepGuide
Metrics to Evaluate a Classification Machine Learning Model
A study case of credit card fraud- 26794Murphy ≡ DeepGuide
ROI Worship Can Be Bad For Business
Watch out for these three ways too much of a good thing can be dangerous- 26409Murphy ≡ DeepGuide
Real World Use Cases: Strategies that Will Bridge the Gap Between Development and Productionizing
Data science demonstrates its value when applied to practical challenges. This article shares insights gained from hands-on machine...- 28878Murphy ≡ DeepGuide
Efficient Metric Collection in PyTorch: Avoiding the Performance Pitfalls of TorchMetrics
Metric collection is an essential part of every machine learning project, enabling us to track model performance and monitor training progress. Ideally, metrics should be collected and computed without introducing any additional overhead to the training p- 24523Murphy ≡ DeepGuide
We look at an implementation of the HyperLogLog cardinality estimati
Using clustering algorithms such as K-means is one of the most popul
Level up Your Data Game by Mastering These 4 Skills
Learn how to create an object-oriented approach to compare and evalu
When I was a beginner using Kubernetes, my main concern was getting
Tutorial and theory on how to carry out forecasts with moving averag