Mastering Neural Networks and Model Regularization
Completed by Mahi Tushar Mehta
October 11, 2026
16 hours (approximately)
Mahi Tushar Mehta's account is verified. Coursera certifies their successful completion of Mastering Neural Networks and Model Regularization
What you will learn
Build neural networks from scratch and apply them to real-world datasets like MNIST.
Apply back-propagation for optimizing neural network models and understand computational graphs.
Utilize L1, L2, drop-out regularization, and decision tree pruning to reduce model overfitting.
Implement convolutional neural networks (CNNs) and tensors using PyTorch for image and audio processing.
Skills you will gain
- Category: Deep Learning
- Category: Convolutional Neural Networks
- Category: Supervised Learning
- Category: Model Training
- Category: Applied Machine Learning
- Category: PyTorch (Machine Learning Library)
- Category: Model Optimization
- Category: Decision Tree Learning
- Category: Model Evaluation
- Category: Artificial Neural Networks
- Category: Machine Learning
