In today&#39;s episode, we delve into a popular topic at Databricks: building recommendation engines. We&#39;ll guide you on how to plan such projects, measure your model&#39;s success, suggest effective algorithms, and cover many other insights! <h1>Sponsors</h1><ul><li><a href="https://topenddevs.com/resume" rel="nofollow">Chuck&#39;s Resume Template</a></li><li><a href="https://topenddevs.com/book-club" rel="nofollow">Developer Book Club starting</a></li><li><a href="https://topenddevs.com/sign_up" rel="nofollow">Become a Top 1% Dev with a Top End Devs Membership</a></li></ul> Advertising Inquiries: <a href='https://redcircle.com/brands'>https://redcircle.com/brands</a> Privacy & Opt-Out: <a href='https://redcircle.com/privacy'>https://redcircle.com/privacy</a>

Confidence as Data Scientist - ML 130

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.