Artificial Neural Networks (ANN)

Most folks consider ANN`s synonymous with Neural Networks. However, both aren`t the same. Instead, an ANN is a type of Neural Network. ANNs are sometimes also referred as MLPs by the industry.

This course provides a solid foundation for a career in Artificial Neural Networks (ANN) and deep learning. We explain how ANN can be applied to create predictive models capable of informing financial decisions. We take you step by step through the process of building ANN models in Python until you can create your own ANN algorithms. This course can help you to predict financial shifts in time to plan for them.

ANN is one of the most popular ML algorithms used by Data Scientists today. The course begins with the basic introduction to neural networks covering important concepts such as perceptron, activation function, sigmoid neuron, NN architecture and logic. We then move to building ANNs, including data analysis, evaluation, error estimation and hypertuning before using the model to make predictions. This course explains the Business Scenarios and Best Business Practices, where ANN models have been successful. The course makes you an expert in ANN giving you a competitive edge over your peers in ML and Prediction Analytics.

Trainers:
Experts from the field of Maths, Data Science and Management, each with over 25 years of International experience working in EU/US/Australia

What you'll learn
:- Get a solid understanding of Artificial Neural Networks (ANN) and Deep Learning
:- Learn usage of Keras and Tensorflow libraries
:- Understand the business scenarios where Artificial Neural Networks (ANN) is applicable
:- Building and Train an Artificial Neural Networks (ANN) in Python
:- Use Artificial Neural Networks (ANN) to make predictions

Who this course is for:
:- People pursuing a career in Data Science
:- Anyone curious to master ANN from Beginner level in short span of time
:- Data Analysts and Engineers
:- University Students
:- Scientists and Researchers