Adventures in Machine Learning By cover art

Adventures in Machine Learning

By: Charles M Wood
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  • Summary

  • 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.
    Copyright Charles M Wood
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Episodes
  • Redefining Data Science Roles: Beyond Technical Skills and Traditional Job Descriptions - ML 155

    Redefining Data Science Roles: Beyond Technical Skills and Traditional Job Descriptions - ML 155
    Jun 20 2024
    In today's episode, Michael Berk and Ben Wilson dive deep into the intricacies of technical interviews for machine learning roles. They discuss the importance of assessing candidates' genuine knowledge of traditional and deep learning models and the value of being candid about one's expertise.
    They explore how technical skills, particularly in applied machine learning, are evaluated with a focus on their impact on business outcomes. Michael and Ben also address the common misalignments between job descriptions and the actual skills required, stressing the need for problem-solving capabilities and critical thinking over memorized knowledge.
    Additionally, they delve into the roles within data science—analysts, applied ML specialists, and researchers—highlighting the importance of fitting the right skills to the right job. They also touch on the evolving expectations and frustrations with the current hiring process, offering insights on how it can be improved.
    Stay tuned as they unpack these topics and more, including valuable tips for showcasing your skills effectively on resumes, and the significance of asking insightful questions during interviews. Whether you’re an aspiring data scientist or a seasoned professional, this episode is packed with practical advice and industry insights you won’t want to miss!

    Socials
    • LinkedIn: Ben Wilson
    • LinkedIn: Michael Berk


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    58 mins
  • Balancing Theoretical Knowledge with Hands-on Experience - ML 154

    Balancing Theoretical Knowledge with Hands-on Experience - ML 154
    Jun 13 2024
    Michael Berk and Ben Wilson from Databricks are joined by Brooke Wenig, who has a fascinating background in distributed machine learning. Today’s conversation dives deep into the intersection of AI, environmental science, and career transitions. They explore how individuals like Michael transformed their careers from environmental science to AI, leveraging existing expertise in innovative ways. Ben shares insights on leaping from non-technical roles to data science by embracing automation with Python and machine learning.
    We tackle the critical shift in roles, the balance between education and hands-on experience, and the growing disparity between academia and industry. Brooke brings valuable perspectives on project scoping, from aligning success criteria to ensuring real-world value. The discussion revolves around augmenting existing roles with AI, common pitfalls, and transitioning proofs of concept to production.
    They also explore the practical applications of language models, the debate over open versus closed source models, and the future of AI in various industries. With a focus on collaboration, the traits of top data scientists, and the implications of integrating AI into non-tech fields, this episode is packed with insights and tips for anyone looking to navigate the exciting world of AI and machine learning.
    Join them as they delve into these topics and more, discussing the evolving landscape of AI and how it's shaping careers and industries alike.

    Socials
    • LinkedIn: Brooke Wenig


    Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
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    1 hr and 8 mins
  • AI in Security: Revolutionizing Defense and Outsmarting Attackers in the Digital Era - ML 153

    AI in Security: Revolutionizing Defense and Outsmarting Attackers in the Digital Era - ML 153
    Jun 6 2024
    Michael Berk and Ben Wilson join cybersecurity expert Daniel Miessler to delve into the cutting-edge world of AI and cybersecurity. They discuss the evolving tactics of attackers, from specialized targeting to AI-driven data collection. The episode tackles dynamic risk assessment, the arms race between attackers and defenders, and the role of open-source models in security.
    They explore AI's potential to monitor, defend, and even augment human efforts against security threats, touching on both the opportunities and ethical challenges. They also examine AI's role in protecting against social media scams and phishing attacks, envisioning a future where AI acts as our digital guardian.
    Whether you're in cybersecurity, development, or simply curious about AI's impact on security, this episode is packed with valuable insights. Stay tuned for a fascinating discussion!


    Socials
    • LinkedIn: Daniel Miessler


    Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
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    1 hr and 18 mins
Career Success Economics
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