Ementorhub

What you'll learn

Understand the concepts of perceptrons and multi-layer neural networks.

Apply training techniques, including backpropagation and regularization.

Analyze convolutional neural networks for image and video analysis.

Evaluate and create deep learning projects using frameworks like TensorFlow and Keras.

Skills you'll gain

Artificial Neural Networks

Deep Learning

Tensorflow

Linear Algebra

Keras (Neural Network Library)

Computer Vision

Machine Learning Methods

Image Analysis

Artificial Intelligence and Machine Learning (AI/ML)

Network Architecture

There are 6 modules in this course

The course then advances to artificial neural networks and their real-world applications, drawing inspiration from the human brain's architecture. You'll gain practical insights into input and output layers, the Sigmoid function, and key datasets like MNIST. Specialized topics such as feed-forward networks, backpropagation, and regularization techniques, including dropout strategies and batch normalization, are thoroughly covered. You'll also be introduced to powerful frameworks like TensorFlow and Keras. The course concludes with an in-depth study of convolutional neural networks (CNNs), focusing on their applications and principles for image and video analysis. This course is ideal for tech professionals and students with a basic understanding of programming and mathematics, particularly linear algebra, calculus, and basic probability.

Artificial Neural Networks-Introduction

ANN - Feed Forward Network

Backpropagation

Regularization

Convolution Neural Networks