Recommender Systems with Machine Learning

Recommender Systems with Machine Learning

Build Recommender Systems for Real World Applications using Machine Learning

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What you'll learn

• • Learn the about basics of recommender systems
• • Learn the basics impact of recommender systems with integrated artificial intelligence
• • Learn about the major challenges and applications of recommender systems
• • Learn the basic taxonomy of recommender systems
• • Learn the impact of overfitting, underfitting, bias and variance
• • Learn the fundamental concepts of content based filtering and collaborative filtering
• • Learn the hands-on development of recommender system using machine learning topologies with python
• • Learn building the recommender system for various recommender system applications such as Spotify song recommending systems using machine learning and python
• • Hands on experience to build content-based recommender systems with machine learning and python
• • Hands on experience to build item-based recommender systems using machine learning techniques and python
• • Learn to model k-nearest neighbors-based recommender engine for various types of applications of recommender systems in python
• • And much more…

Comprehensive Course Description:

Have you ever thought how YouTube adjust your feed as per your favorite content?

Ever wondered! Why is your Netflix recommending you your favorite TV shows?

Have you ever wanted to build a customized recommender system for yourself?

If Yes! Than this is the course you are looking for.

You might have searched for many relevant courses, but this course is different!

This course is a complete package for the beginners to learn the basics of recommender systems, its applications and building it from scratch by using machine learning with python. Every module has engaging content covering necessary theoretical concepts with a complete practical approach is used in along with brief theoretical concepts. At the end of every module, we assign you a quiz, the solution to the quizzes is also available in the next video.

We will be starting with the theoretical concepts of recommender systems, after providing you the basic knowledge of recommender systems. You will be able to learn about the important taxonomies of recommender systems which are actually the basic building block of it.

This complete package will enable you to learn the basic to advance mechanism of developing recommender system by using machine learning with python. We’ll be using Python as a programming language in this course, which is the hottest language nowadays if we talk about machine leaning. Python will be taught from elementary level up to an advanced level so that any machine learning concept can be implemented.

This comprehensive course will be your guide to learning how to use the power of Python to evaluate your recommender systems datasets based on user ratings, user choices, music genres, categories of movies, and their year of release. Moreover, a practical approach will be adopted to build content-based filtering and collaborative filtering techniques for recommender systems where hands on experience will be developed.

We’ll learn all the basic and necessary concepts for the applied recommender systems models along with the machine learning models. Moreover, various projects have been included in this course to develop a very useful experience for yourselves.

Machine learning has been ranked as one of the hottest jobs on Glassdoor, and the average salary of a machine learning engineer is over $110,000 in the United States, according to Indeed! Machine Learning is a rewarding career that allows you to solve some of the world's most interesting problems!

This course is designed for both beginners with some programming experience or even those who know nothing about Data Analysis, ML and RNNs!

This comprehensive course is comparable to other Recommender Systems using Machine Learning courses that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost in only one course! With over 6 hours of HD video lectures that are divided into many videos and detailed code notebooks for every address this is one of the most comprehensive courses for Recommender Systems using Machine Learning on Udemy!

Why Should You Enroll in This Course?

The course is crafted to help you understand not only the role and impact of recommender systems in real world applications but it provides a very unique hands on experience on developing complete recommender systems engines for your customized dataset by using various projects. This straightforward learning by doing course will help you in mastering the concepts and methodology with regards to Python.