Course Overview
1h 34m | 14 Videos | 40974 Views | 
Intermediate Deep Learning is a new part of Machine Learning, which has been introduced with the objective of moving Machine Learning closer to Artificial Intelligence.
Machine learning is a scientific discipline that explores the construction and study of algorithms that can learn from data. Such algorithms operate by building a model from example inputs and using that to make predictions or decisions, rather than following strictly static program instructions. Machine learning is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making.
Through this training we are going to learn and apply concepts of neural networks and optimization techniques in building a deep learning application.
The training will include the following;
1. What is a neural network?
2. Functioning of a single node and multi node neural network.
3. Understanding forward propagation and back propagation.
4. Activation functions
5. Optimization techniques
6. Some Deep Learning libraries
7. Introduction to Keras and Tensorflow
8. Demo on building a Deep Learning Application.
Target Customers:
- Anyone who wants to learn about data and analytics
- Data Engineers
- Analysts
- Architects
- Software Engineers
- IT operations
- Technical managers
Pre-Requisites:
- Basic knowledge of machine learning required
- Basic knowledge of programming and statistics
