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The Openlayer Blog

Our thoughts on ML

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Company

Navigating the chaos: why you don’t need another MLOps tool

And how to build trustworthy AI

Openlayer • November 29th, 2023

5 minute read
Navigating the chaos: why you don’t need another MLOps tool
Data-centric
Model quality

What is data-centric AI: 3 reasons to pay attention to it

The trend in AI

Gustavo Cid • November 23rd, 2023

5 minute read
What is data-centric AI: 3 reasons to pay attention to it
Explainability

SHAP demystified: understand what Shapley values are and how they work

From game theory to machine learning

Gustavo Cid • November 1st, 2023

8 minute read
SHAP demystified: understand what Shapley values are and how they work
Error analysis
Model quality

Error analysis x Model monitoring: how are they different?

Show me your ML development pipeline and I'll tell you who you are

Gustavo Cid • August 15th, 2023

5 minute read
Error analysis x Model monitoring: how are they different?
Error analysis
Explainability

Error analysis in machine learning: going beyond predictive performance

Going beyond predictive performance

Gustavo Cid • July 10th, 2023

7 minute read
Error analysis in machine learning: going beyond predictive performance
Data quality
Data science

Data labeling and relabeling in machine learning

The never-ending process in data science

Sundeep Teki • June 26th, 2023

5 minute read
Data labeling and relabeling in machine learning
Data science
Data-centric
Testing

Detecting data integrity issues in machine learning

Methods and tools for data quality assurance

Gustavo Cid • June 20th, 2023

6 minute read
Detecting data integrity issues in machine learning
Data science
Machine learning

How to generate synthetic data for machine learning projects

Solving the data gap

Sundeep Teki • June 13th, 2023

10 minute read
How to generate synthetic data for machine learning projects
Model quality
Data science

Baseline models demystified: a practical guide

Start simple to get far

Gustavo Cid • June 5th, 2023

7 minute read
Baseline models demystified: a practical guide
Company
Development

How we built our public site with Next.js, Sanity and Emotion

Developing fast and reliably

Rex Garland • May 30th, 2023

6 minute read
How we built our public site with Next.js, Sanity and Emotion
Explainability
Model quality
Error analysis

A beginner’s guide to evaluating machine learning models beyond aggregate metrics

A high accuracy is not enough

Gustavo Cid • May 23rd, 2023

5 minute read
A beginner’s guide to evaluating machine learning models beyond aggregate metrics
Machine learning
Explainability

How LIME works | Understanding in 5 steps

Leveraging how LIME works to build trustworthy ML

Gustavo Cid • May 16th, 2023

7 minute read
How LIME works | Understanding in 5 steps
Company

Openlayer raises $4.8m seed round to build guardrails for AI

Read about our financing round led by Quiet Capital

Openlayer • May 4th, 2023

4 minute read
Openlayer raises $4.8m seed round to build guardrails for AI
Data science
Machine learning

The importance of model versioning in machine learning

Doing iterations right

Oghenefejiro Esosuota • March 14th, 2023

5 minute read
The importance of model versioning in machine learning
Company
Explainability
Error analysis
Data-centric

The race to put AI to work

A tipping point or hype for businesses and environmental, social, and corporate governance (ESG)?

Vikas Nair • June 28th, 2022

10 minute read
The race to put AI to work
Data science

Why every company needs citizen data scientists

Spreading the data knowledge

Andres Soto Villaverde • June 22nd, 2022

7 minute read
Why every company needs citizen data scientists
Data science
Data quality

Surefire ways to identify data drift

Avoiding silent failure in production

Sundeep Teki • May 25th, 2022

6 minute read
Surefire ways to identify data drift
Model quality
Machine learning

Debugging models with the bias-variance trade-off

Systematically boosting model performance

Gustavo Cid • May 23rd, 2022

7 minute read
Debugging models with the bias-variance trade-off
Machine learning

Understanding each piece in the ML infrastructure stack

Making sense of ML systems

Gourav Singh Bais • May 19th, 2022

10 minute read
Understanding each piece in the ML infrastructure stack
Company

Openlayer named to the 2022 CB Insights AI 100 list of most innovative startups

Recognition for the accomplishments in the AI dev tooling space

Openlayer team • May 17th, 2022

2 minute read
Openlayer named to the 2022 CB Insights AI 100 list of most innovative startups
Explainability

The roads toward explainability

Shedding light on black-box ML models

Gustavo Cid • May 11th, 2022

6 minute read
The roads toward explainability
Model quality
Data-centric

Understanding and measuring data quality

The key ingredient for high-quality models

Sundeep Teki • April 25th, 2022

6 minute read
Understanding and measuring data quality
Machine learning

Ensemble learning 101

Stacked models, bagging, and boosting

Gustavo Cid • April 21st, 2022

6 minute read
Ensemble learning 101
Data science
Machine learning

The challenge of becoming a full-stack data scientist

Mastering the full ML lifecycle

Roel Peters • April 18th, 2022

7 minute read
The challenge of becoming a full-stack data scientist
Machine learning
NLP

The representation of meaning

The idea that revolutionized a whole field

Gustavo Cid • April 13th, 2022

9 minute read
The representation of meaning
Big data

10 examples of using Python for big data analysis

Exploring some of the most powerful Python modules for data analysis

Christopher Collins • April 11th, 2022

15 minute read
10 examples of using Python for big data analysis
Machine learning

Mental models for ML products

Avoid missing the forest for the trees with mental models

Gustavo Cid • April 5th, 2022

5 minute read
Mental models for ML products
Explainability

Anchor your predictions

Using Anchors to understand your model's results

Matheus Dias • March 31st, 2022

5 minute read
Anchor your predictions
Machine learning
Model quality

Dealing with class imbalance - Part 2

Evaluating models on unbalanced datasets

Gustavo Cid • March 28th, 2022

8 minute read
Dealing with class imbalance - Part 2
Machine learning
Model quality

Dealing with class imbalance - Part 1

Learning with unbalanced datasets

Gustavo Cid • March 22nd, 2022

6 minute read
Dealing with class imbalance - Part 1
Explainability
Fairness

3 differences between ML in production and in academia

Going beyond ML models and algorithms

Gustavo Cid • March 15th, 2022

5 minute read
3 differences between ML in production and in academia
Model quality
Testing

Testing and its many guises

Understand the need for testing and learn three ML testing frameworks to help you ship with confidence

Gustavo Cid • March 10th, 2022

8 minute read
Testing and its many guises
Machine learning
Model quality

Model evaluation in machine learning

Understanding the true purpose of model evaluation in the quest for high-quality models

Gustavo Cid • February 22nd, 2022

8 minute read
Model evaluation in machine learning
Company

Building the future of ML

The path towards performant and explainable machine learning

Gabriel Bayomi • February 17th, 2022

5 minute read
Building the future of ML