Byte-Sized-Chunks: Recommendation Systems

Grab this amazing opportunity to learn how to build movie recommendation system in Python.

This course will provide you with all the practical knowledge related recommendation system in python. Also, it’ll help you in understanding the system complexities. Each and every concept in this course has been visually described and elaborated,  in order to make it easy for you to understand and learn.

This course has 20 videos in total and will take you through all of these in maximum 5 hours. You can watch the videos at your own pace and accordingly can raise doubts or questions if you get stuck. For enrollment in this course all you need is understanding of undergraduate level mathematics, a bit of Python related knowledge would also be quite helpful.

Following concepts have been properly covered in this course:-

• Recommendation Engines
• Content based filtering
• Collaborative Filtering
• Neighborhood models – also known as Memory based approaches
• Latent factor methods identifying hidden factors that influence users from user history.
• Matrix Factorization
• Many modern recommendation systems including Netflix
• Recommendation Systems in Python!
• Movie lens
• Use of Pandasto read and play around with the data.
• Also learn how to use Scipy and Numpy

On completion of this course:

• You’ll be able to identify use-cases for recommendation systems
• You’ll be able to Design and Implement recommendation systems in Python
• You’ll be able to Understand the theory underlying this important technique in machine learning

Some exceptional benefits associated with this course enrollment are:

• Quality course material
• Instant & free course updates
• Access to all Questions & Answers initiated by other students as well
• Personalized support from the instructor’s end on any issue related to the course
• Few free lectures for a quick overview

Grab this highly affordable, detailed and exclusive course from IT & Software category today itself!