Lasso

Exhibia was nominated as one of the best startups in Miami in Startups of the Year hosted by HackerNoon.  This is an interview with their CEO. 

"90% of software startups fail because no one wants to use them" according to Exhibia CEO Miko Lasso

Ted Lasso's leadership style is rarely seen in media. 

What traits can we learn from Ted to make us successful leaders?

Ted Lasso’s Leadership Lessons Made Me a Successful Leader

Regression analysis is a statistical technique that models and approximates the relationship between a dependent and one or more independent variables. This article will quickly introduce three commonly used regression models using R and the Boston housing data-set: Ridge, Lasso, and Elastic Net.

An Introduction to Ridge, Lasso, and Elastic Net Regression

For many years, programmers have tried to solve extremely complex computer science problems using traditional algorithms which are based on the most basic condition statement: if this then that. For example, if the email contains the word “free!” it should be classified as spam.

Practical machine learning: Ridge Regression vs. Lasso

This article explores four advanced attack patterns, backed by the latest research, that have virtually no overlap with the “ignore previous instructions”

Exploring and Explaining The New Frontiers of Advanced Prompt Injection

This article investigates how the July 2024 CrowdStrike crash exposed the fragility of automated AI‑driven security systems and their global fallout.

The $10 Billion Logic Error: What Happens When Security Moves Faster Than Sanity

This paper provides a comprehensive analysis of automatic database management system (DBMS) tuning. 

Smarter Systems, Less Hassle: Inside DBMS Auto-Tuning

Pruning techniques like feature projection, ranking, and reduction help reduce DBMS tuning complexity, improving efficiency in data collection and training.

Pruning Techniques for Reducing Workload and Configuration Space Complexity

Learn about configuration-level pruning techniques for DBMS tuning, including SRCC, PCA, LASSO, Random Forest, and HeSBO. 

How Configuration-level Pruning Reduces Optimization Time in DBMS Tuning

Discover how MagicEraser.Pro simplifies photo editing by allowing users to easily remove unwanted elements like people, logos, and background clutter

MagicEraser.Pro Review: Effortlessly Enhance Your Photos With AI Magic Eraser

In this study, researchers attempt to characterize the region where large language models transition from in-context learners to translation models.

Where does In-context Translation Happen in Large Language Models: Conclusion

LLMs are data models trained on colossal amounts of text data, ingesting books, articles, code, and other forms of written content.

LASSO

lassoload.com

51-200 emps

Since 2014

LASSO (KIDZW)

EVERGREEN INDEX #6833

Lasso's stories on HackerNoon

"90% of software startups fail because no one wants to use them" according to Exhibia CEO Miko Lasso

Ted Lasso’s Leadership Lessons Made Me a Successful Leader

An Introduction to Ridge, Lasso, and Elastic Net Regression

Practical machine learning: Ridge Regression vs. Lasso

Exploring and Explaining The New Frontiers of Advanced Prompt Injection

The $10 Billion Logic Error: What Happens When Security Moves Faster Than Sanity

Smarter Systems, Less Hassle: Inside DBMS Auto-Tuning

Pruning Techniques for Reducing Workload and Configuration Space Complexity

How Configuration-level Pruning Reduces Optimization Time in DBMS Tuning

MagicEraser.Pro Review: Effortlessly Enhance Your Photos With AI Magic Eraser

Where does In-context Translation Happen in Large Language Models: Conclusion

Holodeck Heroes: Building AI Companions for the Final Frontier

Lasso's Related Companies

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Reviews About Lasso

Lasso WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!

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Classic

Newspaper

Minty

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Neon Noir

Minty

HN StartUps

LASSO

lassoload.com

51-200 emps

Since 2014

LASSO (KIDZW)

EVERGREEN INDEX #6833

Lasso's stories on HackerNoon

"90% of software startups fail because no one wants to use them" according to Exhibia CEO Miko Lasso

Ted Lasso’s Leadership Lessons Made Me a Successful Leader

An Introduction to Ridge, Lasso, and Elastic Net Regression

Practical machine learning: Ridge Regression vs. Lasso

Exploring and Explaining The New Frontiers of Advanced Prompt Injection

The $10 Billion Logic Error: What Happens When Security Moves Faster Than Sanity

Smarter Systems, Less Hassle: Inside DBMS Auto-Tuning

Pruning Techniques for Reducing Workload and Configuration Space Complexity

How Configuration-level Pruning Reduces Optimization Time in DBMS Tuning

MagicEraser.Pro Review: Effortlessly Enhance Your Photos With AI Magic Eraser

Where does In-context Translation Happen in Large Language Models: Conclusion

Holodeck Heroes: Building AI Companions for the Final Frontier

Lasso's Related Companies

1991

1610B

1977

877B

1972

301.5B

1980

197.1B

1967

181.7B

1980

163.3B

Representing this company? Click here to claim and customize this page!

Reviews About Lasso

Lasso WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!

Light-Mode

Classic

Newspaper

Minty

Dark-Mode

Neon Noir

Minty

HN StartUps