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מתחיל 5 June 2026 22:38

נגמר 5 June 2026

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Design and Build Custom Neural Networks

Master custom neural network design by comparing CNNs, RNNs, and Transformers, then build optimized PyTorch architectures with proper layers, activations, and regularization techniques.
Coursera via Coursera

Coursera

2874 קורסים


2 hours 2 minutes

שדרוג אופציונלי זמין

Not Specified

התקדמות בקצב שלך

Paid Course

שדרוג אופציונלי זמין

סקירה כללית

This course teaches you how to evaluate and design custom neural network architectures for real machine-learning tasks. You start by learning how to compare common model families—such as CNNs, RNNs, and Transformers—and match them to task needs, data patterns, and compute limits.

You then learn how to construct custom architectures using layers, activations, and regularization techniques that improve generalization and training stability. Through videos, readings, hands-on practice, and guided coach support, you build models in PyTorch and test how design choices affect performance.

By the end of the course, you can confidently select topologies, justify architectural decisions, and design models ready for real-world deployment.

סילבוס

  • Design and Build Custom Neural Networks
  • This course teaches you how to evaluate and design custom neural network architectures for real machine-learning tasks. You start by learning how to compare common model families—such as CNNs, RNNs, and Transformers—and match them to task needs, data patterns, and compute limits.

נלמד על ידי

ansrsource instructors


נושאים

Artificial Intelligence