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: Supervised Learning
- Category: Model Training
- Category: Applied Machine Learning
- Category: Model Optimization
- Category: Artificial Neural Networks
- Category: Machine Learning
- Category: PyTorch (Machine Learning Library)
- Category: Decision Tree Learning
- Category: Model Evaluation
- Category: Convolutional Neural Networks
- Category: Deep Learning
