Mastering Neural Networks and Model Regularization

The course "Mastering Neural Networks and Model Regularization" dives deep into the fundamentals and advanced techniques of neural networks, from understanding perceptron-based models to implementing cutting-edge convolutional neural networks (CNNs). This course offers hands-on experience with real-world datasets, such as MNIST, and focuses on practical applications using the PyTorch framework. Learners will explore key regularization techniques like L1, L2, and drop-out to reduce model overfitting, as well as decision tree pruning. What makes this course unique is its emphasis on building ne…