A strong portfolio starts with a solid understanding of the fundamentals. Focus on key areas like linear algebra, calculus, probability, statistics, and programming languages such as Python or R. Demonstrating proficiency through projects that apply these concepts will show your preparedness for machine learning challenges.
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