Artificial Neural Networks tutorial - theory & applications
What you'll learn
- Basics of Artificial Neural Network (ANN)
- Terms and defintions associated with ANN
- How does ANN work
- How to solve binary classification problem using artificial neural network in R
- How to solve multi level classification problem using artificial neural network in R
- Data treatment guideline for using ANN
- Pros and Cons of Neural Network
Course content
- Preview01:15
- 01:23How to study this course?
- 07:03What is neural network? Motivation behind neural network
- 07:12Terms Associated with Neural Network
- Preview09:58
- 05:24Data Preprocessing required to apply ANN
Requirements
- Should know basic R programming
- Basic computer skills
- Ability to locate resource supplied with this course on Udemy platform
Description
This course aims to simplify concepts of Artificial Neural Network (ANN). ANN mimics the process of thinking. Using it's inherent structure, ANN can solve multitude of problem like binary classifications problem, multi level classification problem etc.
The course is unique in terms of simplicity and it's step by step approach of presenting the concepts and application of neural network.
The course has two section
-------------------------------------------------------
Section 1 : Theory of artificial neural network
--------------------------------------------------------
- what is neural network
- Terms associated with neural network
- What is node
- What is bias
- What is hidden layer / input layer / output layer
- What is activation function
- What is a feed forward model
- How does a Neural Network algorithm work?
- What is case / batch updating
- What is weight and bias updation
- Intuitive understanding of functioning of neural network
- Stopping criteria
- What decisions an analyst need to take to optimize the neural network?
- Data Pre processing required to apply ANN
-------------------------------------------------------
Section 2 : Application of artificial neural network
--------------------------------------------------------
- Application of ANN for binary outcome
- Application of ANN for multi level outcome
- Assignment of ANN - learn by doing
Who this course is for:
- Analytics professionals, who are trying to learn artificial neural network
- Students, who are trying to make their career into analytics domain
- Finance professionals, who want to get first hand exposure of artificial neural network concepts
Instructor
![Gopal Prasad Malakar](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.3 Instructor Rating
- 9,837 Reviews
- 107,632 Students
- 17 Courses
I am a seasoned Analytics professional with 20+ years of professional experience. I have industry experience of impactful and actionable analytics, data science, decision strategy and enterprise wise data strategy.
I am a keen trainer, who believes that training is all about making users understand the concepts. If students remain confused after the training, the training is useless. I ensure that after my training, students (or partcipants) are crystal clear on how to use the learning in their business scenarios.
My expertise is in Credit Card Business, Scoring (econometrics based model development), score management, loss forecasting, business intelligence systems like tableau /SAS Visual Analytics, MS access based database application development, Enterprise wide big data framework and streaming analysis.
Please refer to my course for
- SAS / R program details (syntax and options)
- SAS / R output deep dive
- Practical usage in Industrial situation