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S27:E3 - Helping You Build Machine Learning Products (Pau Labarta Bajo)
Mar 27, 2024
Pau Labarta Bajo, a Math turned ML expert, discusses transitioning from Excel to Python, importance of data in ML, essential skills for new devs. Talks about ML vs Stats, challenges in deploying models, leveraging domain knowledge in coding, freelancing as an ML engineer, and learning through failures in coding projects.
46:08
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Quick takeaways
- Transitioning from Excel to Python is crucial for entering the field of machine learning.
- Understanding the distinction between statistics and machine learning helps in choosing suitable problem-solving approaches.
Deep dives
Transition from Mathematics to Applied Statistics and Data Science
Starting with a passion for solving problems in his childhood, Paul transitioned from competing in mathematical contests to studying mathematics in university. Feeling the need for real-world applications, he shifted to work as a quantitative analyst in a bank in Vienna, focusing on building statistical models for financial derivatives risk assessment.
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