Louis M

Louis is a seasoned technology executive with over 20+ years of experience in leading and managing teams, building products, and implementing open-source technologies. He is certified in building Crypto currencies applications and has a proven track record of effectively leading teams of over 100+ individuals, including experience leading through a management layer (manager of managers). Louis possesses vital emotional intelligence, allowing him to lead a diverse group of engineers and managers at varying stages of their careers. He has experience leading teams through complex compliance certifications, such as FedRAMP, PCI, SOC2, ISMAP & HIPAA. He has 10+ years of security experience dealing with web systems, Cloud, SaaS, compliance, corp IT, infrastructure, and embedded devices. Louis has a solid understanding of cross-functional engineering organizations and significant experience building diverse and inclusive teams. He has superb communication skills and can articulate a compelling security vision. Most recently, Louis served as the CTO of Metabolicliving, where he led the engineering team to become a high-performing, on-time delivery cross-functional team and collaborated with Executive Leadership to develop & manage product strategy, roadmaps, and technical execution plans. Before that, he served as the CTO of Burnalong, a health and fitness tech startup. He single-handedly built the AWS infrastructure, on-site cross-functional engineering team, remote developers, and QA. He also created an internship program to cultivate new talent and grow the technical organization.

Avoiding Pitfalls in Machine Learning: Common Errors and How to Prevent Them

Avoiding Pitfalls in Machine Learning: Common Errors and How to Prevent Them

Learn how to avoid common pitfalls in machine learning, including overfitting, feature selection, data leakage, and continuous learning. Improve your models and

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How to Recover When Machine Learning Fails: A Troubleshooting Guide

How to Recover When Machine Learning Fails: A Troubleshooting Guide

Discover practical tips and tricks to troubleshoot common failures in machine learning. Get back on track to success! By Louis M. Read more.

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Understanding Overfitting and Underfitting in Machine Learning Models

Understanding Overfitting and Underfitting in Machine Learning Models

Unravel the mysteries of overfitting and underfitting in machine learning. Find strategies to strike the perfect balance for optimal model performance.

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Machine Learning Failures: Case Studies and Lessons Learned

Machine Learning Failures: Case Studies and Lessons Learned

Discover the failures of machine learning in various industries. Learn valuable lessons from chatbot chaos, misclassifying mayhem, and image recognition blunder

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