There has been a tremendous boom in the applications of Computer Vision and Natural Language Processing now a days.
The applications of Computer Vision range from understanding the environment in a Self - Driving Car to build Facial Recognition based Attention Systems for classrooms in Education Industry. Natural Language Processing on the other hand helps us to build ChatBots.
Computer Vision systems deal with high variety and volume of data, specifically images or videos. It is represented as bits and blobs which is hard to explain to a machine. As a result, these systems need intricate techniques to make sense of the data and then make data driven decisions.
This course is designed to give you a taste of how the neural networks works which are the basic building blocks behind any computer vision or natural language processing applications.
This is a beginner friendly course, so it does not assume any familiarity with Computer Vision or Deep Learning algorithms. But, this course assumes that you are comfortable with Python programming.
- Welcome to Introduction to Neural Networks
- Getting started with Neural Network
- Exercise : Getting started with Neural Network
- Independent and dependent variables
- Understanding Forward Propogation
- Exercise : Forward Propogation
- Error and Reason for Error
- Exercise : Error and Reason for Error
- Gradient Descent Intuition
- Understanding Math Behind Gradient Descent
- Exercise : Gradient Descent
- Back Propagation
- Exercise : Back Propagation
- Summary of the Module
- Computer Vision
- Natural Language Processing
- Audio Processing
- Where to go from here?
Analytics Vidhya provides a community based knowledge portal for Analytics and Data Science professionals. The aim of the platform is to become a complete portal serving all knowledge and career needs of Data Science Professionals.
Who should take this course?
This course is for people who are looking to get into the field of Computer Vision or Natural Language Processing (NLP) or who wants learn the basics of Neural Networks.
What is the refund policy?
The fee for this course is non-refundable.
Do I get a certificate upon completion of the course?
No, there is no certificate for this course.
What is the fee for this course?
This course is free of cost.
Support for Introduction to Neural Networks course can be availed through any of the following channels: