Welcome to the Recommender Systems in Practice Crash Course in collaboration with Applied Singularity!
As the amount of content on Netflix or products on Amazon increases, consumers are given significantly more choice. However, choosing a single item takes much longer and the process becomes less enjoyable, or even frustrating, for users. A powerful Recommendation System can help users by suggesting and highlighting items that they are most likely going to want or need. These systems also help the platform by ensuring that users complete the transaction or consume the content faster. As such, they are indispensable to organisations and are at the core of AI efforts for multiple companies today.
Recommendation Systems are becoming increasingly sophisticated, incorporating an ensemble of algorithms from Machine Learning, NLP, time-series modelling, and more. In this 6-hour workshop, you will be exposed to the inner workings of Recommender algorithms, see real-world use cases from social media companies, e-commerce companies, streaming content providers, etc, and get hands-on experience building your own Recommender System!
Feel free to ask your questions via Machine learning hub on Global AI Hub Community.
You can check most frequently asked questions about this course.
• Introduction to Recommender Systems
• Types of Recommender Systems – Content-based, Collaborative-based & Hybrid systems
• Important concepts related to Data Analysis & Preprocessing – NLP based concepts like Stemming, Lemmatization
• Statistical concepts – Pearson Correlation, Cosine Similarity etc.
• Various approaches for building Recommender Systems – Matrix Factorization, SVD, Deep Learning etc.
• Recommender Systems in Practice – Amazon, Netflix, LinkedIn, YouTube
• Impact of Personalization & Recommendations
• Can try this – Kaggle Challenge: A task is given based on a dataset. Time limit of 7 days.
• Pros & Cons of Recommendation Systems
• Applied Singularity Quiz
• Exploratory Data Analysis on various datasets
• Hands-on – Content Based, Collaborative (and it’s varieties) Based & Hybrid Implementations
• Brief about the latest advancements in this field, Quiz
• Ethics in building Recommender Systems
Prerequisites for the Workshop:
• Conceptual understanding of Deep Learning
• Basics of NLP
• Stable Internet connection
• Access to Google Collab