Revise and Learn all Your Concepts

Basics

Evolution of Neural Networks

What are Neural Networks?

How does Neural Networks work?

Learning of a Neural Network

Types of Neural Networks

Simple Implementation of a Neural Network

Hyperparameter
Tuning

Learning Rate

Number of Layers

Number of Neurons per Layer

Batch Size

Epoch

Neural Network
Libraries and
Frameworks

TensorFlow

PyTorch

Keras

Caffe

MXNet

Theano

Emerging Trends

Continual Learning

Meta-Learning

Capsule Networks

Graph Neural Networks

Neuroevolution

Fundamentals of
Neural Networks

Inputs

Weighted Sum
- Weighted Sum in Neural Networks
- Neural Network Architecture
Activation Function
- Activation Functions in Neural Networks
- Types of Activation Functions
Output
- Output in Neural Networks
- Output Layer
Sigmoid
- Sigmoid Function
- Sigmoid Function in TensorFlow
ReLU (Rectified Linear Unit)
- ReLU Function
- ReLU Function in TensorFlow
Tanh
- Tanh Function
- Tanh Function in TensorFlow
Leaky ReLU
- Leaky ReLU Function
- Leaky ReLU Function in TensorFlow
Softmax
- Softmax Function
- Softmax Function in TensorFlow
Weights (W)
- Weights in Neural Networks
- Weighted Sum
Biases (b)
- Biases in Neural Networks
- Weighted Sum
Input Layer
- Input Layer
- Neural Network Architecture
Hidden Layers
- Hidden Layers
- Neural Network Architecture
Output Layer
- Output Layer
- Neural Network Architecture
Error Calculation
- Error Calculation in Neural Networks
- Backpropagation
Gradient Computation
- Gradient Computation in Neural Networks
- Backpropagation
Weight and Bias Update
- Weight and Bias Update in Neural Networks
- Optimization Algorithms
Iterative Process
- Iterative Process in Neural Networks
- Training Neural Networks

Interpretability &
Explainability

Saliency Maps

Layer Visualization

Activation Maximization

Concept Activation Vectors

Neural Network
Architectures

Feedforward Neural Networks

Feedforward neural network

Types of Neural Networks

Convolutional Neural Networks (CNNs)

Recurrent Neural Networks (RNNs)

Long Short-Term Memory (LSTMs)

Gated Recurrent Units (GRUs)

Autoencoders

Generative Adversarial Networks (GANs)

Applications of
Neural Networks

Image Classification

Object Detection

Semantic Segmentation

Natural Language Processing

Speech Recognition

Machine Translation

Anomaly Detection

Recommendation Systems