Michael and Ben talk about Prediction Intervals. They discuss how to put intervals around your predictions and then aiming for a certain level of confidence.   Michael and Ben discuss how to put it together and how to use it.  Panel  Ben WilsonMichael Berk  Sponsors  Top End DevsCoaching | Top End DevsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacyBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

Prediction Intervals - ML 056

Machine Learning is growing in leaps and bounds both in capability and adoption. Listen to our experts discuss the ideas and fundamentals needed to succeed as a Machine Learning Engineer.Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

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Matt Van Itallie is the Founder & CEO at Sema. This episode covers a wide range of topics, from the impact of AI and machine learning on software development and educational systems, to the importance of code reviews and career advice in the tech industry. Matt Van Italy shares his diverse experiences in law, consulting, public schools, and the tech sector, emphasizing the value of using data to drive improvements.The conversation also touches on the use of GenAI tools in development and the need for organizations to embrace new technology to stay competitive. They also explore issues such as defense spending, career transitions, and the significance of investing in education and human capital.SponsorsChuck's Resume TemplateDeveloper Book Club Become a Top 1% Dev with a Top End Devs MembershipSocialsLinkedIn: Matt Van ItallieBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

The Impact of AI Tools on Software Development and Quality Assurance - ML 130

Terry Rodriguez is the Co-Founder at Remyx AI. They discuss the challenges and opportunities in deploying and updating AI models for robotics, exploring the potential applications across various industries, and delving into the complexities of conducting experiments and controlling for interaction effects. You'll also hear from industry experts who have worked on recommender algorithms and enhancing content recommendations through experimental workflows and hypothesis testing. Get ready for an insightful and dynamic conversation about the latest developments in the ML landscape!SponsorsChuck's Resume TemplateDeveloper Book ClubBecome a Top 1% Dev with a Top End Devs MembershipSocialsLinkedIn: Terry RodriguezBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

Adaptive Industry ML: Challenges, Automation, and Model Applications - ML 149

Lukas Geiger is a Deep Learning Scientist, open-source developer, and an astroparticle physicist. He shares his experience using machine learning to analyze cosmic ray particles and detect secondary particles. We explore the challenges and opportunities of open source as a business model, the potential of models for edge computing, and the importance of understanding open-source code. Join us as we delve into the intersection of physics, machine learning, and the intricate world of software development.SponsorsChuck's Resume TemplateDeveloper Book ClubBecome a Top 1% Dev with a Top End Devs MembershipSocialsLinkedIn: Lukas GeigerBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

Harnessing Open Source Contributions in Machine Learning and Quantization - ML 148

Nick Schrock is the Founder of Dagster Labs. He is also the Creator of Dagster and the Co-creator of GraphQL. They delve into the world of data engineering, software development, and ML orchestration. In today's episode, they explore the challenges and intricacies of standardizing data movement, handling data access in various systems, and migrating data across different platforms. They share insights on the importance of building a system that spans multiple data platforms, the decision-making process behind tool development, and the impact of lineage in managing and migrating data. Join them as they uncover the complexities of open-source projects, API evolution, and the future of data engineering.SponsorsChuck's Resume TemplateDeveloper Book ClubBecome a Top 1% Dev with a Top End Devs MembershipSocialsLinkedIn: Nick SchrockBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

Data Platform Innovation: Navigating Challenges and Building a Unified Experience - ML 147

Ben and Michael dive into the dynamic relationship between engineers and scientists in the realms of software engineering and physical science. They explore the differences and similarities between these roles, sharing valuable insights on the research and testing processes, the importance of thorough research, the value of teamwork, and the challenges of transitioning between engineering and science. With analogies, real-world examples, and expert perspectives, they shed light on the intricacies of these roles and the considerations for hiring scientists and engineers based on company size and market effects. Tune in for a thought-provoking discussion on finding the optimal path between efficiency and innovation in the world of technology and research!SponsorsChuck's Resume TemplateDeveloper Book ClubBecome a Top 1% Dev with a Top End Devs MembershipBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

Prediction Intervals - ML 056

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