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
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
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Section 1 : Theory of artificial neural network
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- 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
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Section 2 : Application of artificial neural network
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- 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
- 4.3 Instructor Rating
- 12,961 Reviews
- 121,018 Students
- 18 Courses
I am a seasoned analytics professional and the CEO of ProData Science AI Consultancy Pvt Ltd, with over 24 years of professional experience. I specialize in impactful and actionable analytics, data science, decision strategy, and enterprise-wide data strategy.
ProData Science offers outstanding solutions for building machine learning models. These solutions make the model-building process enjoyable, accurate, and efficient.
Additionally, I am a dedicated trainer who believes that effective training ensures users understand the concepts thoroughly. If students remain confused after the training, it is ineffective. I ensure that my students or participants are crystal clear on how to apply their learning in real business scenarios.
My expertise includes:
-- Credit card business
-- Scoring ( Machine learning / econometrics-based model development)
-- Score management
-- Loss forecasting / Time series forecasting
-- Business intelligence solutions such as Tableau, SAS Visual Analytics, Microsoft Power BI etc.
-- Enterprise-wide big data framework and streaming analysis
Please refer to my course for
- Data analysis and Data science using SAS / R / Python
- SAS / R / Python program details (syntax and options)
- SAS / R / Python output deep dive
- Practical usage in Industrial situation