Deep Learning Cheat Sheet
Deep Learning is a part of Machine Learning. Deep Learning Algorithms are inspired by brain function. Although, it’s a subset but below image represents the difference between Machine Learning and Deep Learning. It requires lot of computing power to run Deep Learning models e.g. model of driverless cars.
It can be used in industries like Aerospace, Defence, Medical Research, Industrial Automation, Electronics etc.
This cheatsheet help you to do revision of following concepts in brief:
- Activation Function
- Cross Entropy Loss
- Backpropagation
- Convolutional Neural Networks
- Recurrent Neural Networks
- Reinforcement Learning and Control
This Tips and Tricks document covers following:
- Data Processing: Data augmentation, Batch normalization
- Training a neural network: Epoch, Mini-batch gradient descent, Loss function, Cross-entropy loss, Backpropagation
- Parameter tuning: Xavier initialization, Transfer learning
- Regularization: Weight regularization, Dropout
