Practical AI The mathematics of machine learning
14 snips
Oct 5, 2021 
Tivadar Danka, an educator and content creator in machine learning, dives into how high school math connects to neural networks in this enlightening discussion. He shares his personal journey from academia to practical teaching, illuminating the relevance of calculus, linear algebra, and probability in machine learning. The conversation emphasizes the challenges learners face in grasping these concepts while fostering motivation through real-world applications. Danka also discusses his interactive book aimed at making these crucial theories accessible and engaging for newcomers.
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Timeless Math
- Machine learning moves very fast, making older research less relevant.
- Mathematics, however, is timeless, focusing on the underlying language of algorithms.
Starting Simple
- Start with high school math for machine learning; higher math isn't initially necessary.
- Gradually learn more math as you encounter obstacles in your machine learning journey.
Math as a Language
- Mathematics is the language of machine learning algorithms.
- Your required math level depends on your specific machine-learning role.
