Topic: deep-learning
Modifications to Neural Networks
Purpose Deep Learning is a subset of machine learning and hence it borrows a lot of common use cases from it. Here we will be looking at the…
Backpropagation
Neural Network Topology Training a Neural Network Mathematically Complexity of the Loss Function Example Gradient Descent Questions Gradient…
Convolutional Neural Networks (CNNs)
Purpose CNN - Introduction Challenges in Image Processing CNNs - A specialised architecture for visual data Applications of CNNs Receptive…
Long, Short-term Memory, Gated Recurrent Unit
Bi-Directional RNN Problems with Vanilla RNNs Long, Short-term Memory Networks Characteristics of an LSTM Cell LSTM Cell Common Activation…
Recurrent Neural Networks (RNNs)
Recurrent Neural Networks What are Sequences RNN Formulation Architecture of RNN The flow of information in RNNs is as follows Example…
Convolutional Neural Networks (CNNs) - Industry Applications
Neural networks in industry applications Data Preprocessing: Shape, Size and Form Images - Channels and sizes Question Images…
Feed Forward in Neural Networks
Flow of Information in Neural Networks Comprehension - Count of Pixels Dimensions in a Neural Network Input Vector Weight Matrix Example…
Introduction to Neural Networks
Purpose Artificial Neural Networks (ANNs) Bottlenecks with Neural Networks Deep Learning Applications Human Brain Simplified Human Brain…