Machine Learning Fundamentals — Week 7
Prof. Andrew Chen · MIT OpenCourseWare · 24 students attending
LIVE
01:23:45
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AC
Prof. Andrew Chen
Department of Computer Science · MIT
📽 Presenting: Gradient Descent — Visualization
AI Translation: Active
Die Gradientenabstieg-Methode minimiert die Verlustfunktion durch iterative Anpassung der Gewichte in Richtung des steilsten Abstiegs.
Original: "Gradient descent minimizes the loss function by iteratively adjusting weights toward the steepest descent direction."
In session:
AC
🇺🇸
EJ
🇺🇸
LM
🇩🇪
SR
🇬🇧
TN
🇯🇵
PB
🇧🇷
AK
🇰🇷
MW
🇨🇦
+16
💬 Chat
👥 People
📝 Notes
AC
Prof. Andrew Chen 🇺🇸
Today we'll cover backpropagation and why the chain rule is fundamental to neural network training.
LM
Lucas Müller 🇩🇪
Could you explain the vanishing gradient problem in more detail?
🌐 Translated from German: "Könnten Sie das Problem des verschwindenden Gradienten genauer erklären?"
SR
Sophie Roberts 🇬🇧
The visual explanation really helped — thank you!
TN
Takashi Nakamura 🇯🇵
Can we have the slides shared after the session?
🌐 Translated from Japanese: 「セッション後にスライドを共有できますか？」
EJ
Yes! And Professor — will there be a recording with translated captions available?
AC
Prof. Andrew Chen 🇺🇸
Absolutely — the recording with AI-translated captions in 12 languages will be available within 2 hours. 🎉