Adventures in Machine Learning

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.

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Building, Testing, and Abandoning Software - ML 163

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Published : Aug 22, 2024

Duration : 0 Minutes

Show Notes

In today's episode, Ben and Michael dive deep into the intricacies of software development, innovation, and team dynamics. This episode explores the critical balance between building in-house tools versus leveraging open-source solutions, with real-world examples from Databricks.

They discuss the creation and eventual abandonment of a benchmarking tool for warehouses and discuss the importance of evaluating user demand, effort, and impact before committing to development. They emphasize the role of empathy, constructive feedback, and team collaboration in driving successful projects. They share strategies to influence behavior within organizations, the significance of a blame-free culture, and the art of leading difficult conversations with stakeholders.

From detailed discussions on customer feedback loops to practical advice on automating mundane tasks, this episode is packed with insights that will help you navigate the complex landscape of software development. So sit back, relax, and join us for a thoughtful and engaging conversation on how to turn challenges into opportunities for growth and innovation.

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Adventures in Machine Learning Machine Learning for Movie Scripts - ML 106
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Adventures in Machine Learning ML 005: Transfer Learning for NLP with Daniel Svoboda
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Adventures in Machine Learning The Role of Open Source in Modern Development Practices - ML 170
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Adventures in Machine Learning Monitoring and Evaluating Data Sets ft. Emeli Dral and Elena Samuylova - ML 049
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Adventures in Machine Learning The 3 Essentials for Successful Job Outcomes - BONUS
Adventures in Machine Learning Part 2: Exploratory Data Analysis (EDA) Next Steps - ML 076
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Adventures in Machine Learning

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Building, Testing, and Abandoning Software - ML 163

Show Notes

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