Deep Learning

Deep learning is the branch of machine learning which is based on artificial neural network architecture. An artificial neural network or ANN uses layers of interconnected nodes called neurons that work together to process and learn from the input data.

In a fully connected Deep neural network, there is an input layer and one or more hidden layers connected one after the other. Each neuron receives input from the previous layer neurons or the input layer. The output of one neuron becomes the input to other neurons in the next layer of the network, and this process continues until the final layer produces the output of the network. The layers of the neural network transform the input data through a series of nonlinear transformations, allowing the network to learn complex representations of the input data.

The main applications of deep learning can be divided into computer vision, natural language processing (NLP), and reinforcement learning.

In computer vision, Deep learning models can enable machines to identify and understand visual data. Some of the main applications include the identification and locating of objects within images and videos.

In NLP, the Deep learning model can enable machines to understand and generate human language. Some of the main applications include the generation of essays, translating languages, and sentiment analysis

In reinforcement learning, deep learning works as training agents to take action in an environment to maximize a reward. Some of the main applications of deep learning in reinforcement learning include the training of robots to perform complex tasks such as grasping objects, navigation, and manipulation.

Artificial Intelligence (AI) refers to developing computer systems for performing tasks requiring human intelligence. These systems assess large amounts of data to identify patterns and make logical decisions based on the collected information. The ultimate goal of AI is to create machines to carry out diverse tasks.

Artificial Intelligence techniques refer to a set of methods and algorithms used to develop intelligent systems that can perform tasks requiring human-like intelligence. Some of the widely used ones are:

• Machine Learning.
• Natural Language Processing.
• Computer Vision.
• Deep Learning
• Data Mining
• Robotics.