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Recommender Systems Complete Course Beginner to Advanced - Deep Learning Foundation for Recommender Systems: Strengths and Weaknesses of DL Models
This video discusses in detail the strengths and weaknesses of deep learning models, including non-linear transformations and non-trivial relationships.
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Recommender Systems Complete Course Beginner to Advanced - Deep Learning Foundation for Recommender Systems: VAE Collaborative Filtering
Let's understand the variational autoencoder for collaborative filtering using a representation obtained in the hidden layers.
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Recommender Systems Complete Course Beginner to Advanced - Deep Learning Foundation for Recommender Systems: Neural Collaborative Filtering
In this video, you will learn about another deep learning filter called neural collaborative filtering that uses latent and item latent vectors.
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Recommender Systems Complete Course Beginner to Advanced - Deep Learning Foundation for Recommender Systems: Embeddings and User Context
In this video, we will discuss deep neural network models that are built on the technique of factorization, and interactions between variables and embeddings are taken into account.
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Recommender Systems Complete Course Beginner to Advanced - Deep Learning Foundation for Recommender Systems: Inference Mechanism
In this video, you will learn about the inference mechanisms for generic recommender systems, including individual interests, candidate generation, ranking and filtering, and item similarities.
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Recommender Systems Complete Course Beginner to Advanced - Deep Learning Foundation for Recommender Systems: Inference After Training
In this video, you will learn about the inference mechanisms for generic recommender systems, including training the system to capture information to make recommendations.
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Recommender Systems Complete Course Beginner to Advanced - Deep Learning Foundation for Recommender Systems: Deep Learning in Recommendation systems
As we are aware, recommender systems are migrating from machine learning to deep learning, the reason being to capture non-linear and non-trivial relationships.
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Recommender Systems Complete Course Beginner to Advanced - Deep Learning Foundation for Recommender Systems: Overview
This is a more detailed overview of the deep learning methodology in recommender systems. We will look at the benefits of using deep learning in recommender systems.
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Recommender Systems Complete Course Beginner to Advanced - Deep Learning Foundation for Recommender Systems: Module Introduction
This video briefly introduces deep learning concepts for recommender systems and outlines the concepts to be covered in this module.
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Recommender Systems Complete Course Beginner to Advanced - Project 2: Movie Recommendation System Using Collaborative Filtering: Making Recommendations
We will explore how to make recommendations using collaborative filtering in the movie recommender system.
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Recommender Systems Complete Course Beginner to Advanced - Project 2: Movie Recommendation System Using Collaborative Filtering: KNN Implementation
Here, you will learn how to implement the k-nearest neighbor algorithm in the movie recommender system.
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Recommender Systems Complete Course Beginner to Advanced - Project 2: Movie Recommendation System Using Collaborative Filtering: Create Collaborative Filter
In this lesson, you will learn how to create a collaborative filter for the movie recommender system.
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Recommender Systems Complete Course Beginner to Advanced - Project 2: Movie Recommendation System Using Collaborative Filtering: Active Users and Popular Movies
In this video, we will understand how to calculate our movie project's active users and popular movies.
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Recommender Systems Complete Course Beginner to Advanced - Project 2: Movie Recommendation System Using Collaborative Filtering: Logarithm of Count
In this video, we will explore how to calculate the count of elements using the logarithm function.
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Recommender Systems Complete Course Beginner to Advanced - Project 2: Movie Recommendation System Using Collaborative Filtering: Count
In this lesson, we will create functions to calculate the count of the elements of the project.
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Recommender Systems Complete Course Beginner to Advanced - Project 2: Movie Recommendation System Using Collaborative Filtering: Rating Plot
In this video, you will learn to perform data visualization and analysis for the project using the movies and ratings dataset.
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Recommender Systems Complete Course Beginner to Advanced - Project 2: Movie Recommendation System Using Collaborative Filtering: Dataset Discussion
In this video, we will look at the various libraries we would need to import for this project, including os, math, NumPy, time, and Pandas.
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Recommender Systems Complete Course Beginner to Advanced - Project 2: Movie Recommendation System Using Collaborative Filtering: Project Introduction
This video provides an overview of the movie recommendation system using collaborative filtering.
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Recommender Systems Complete Course Beginner to Advanced - Project 1: Song Recommendation System Using Content-Based Filtering: Find Closest Title
In this lesson, we will try to locate the nearest element to the search, and we will do this using functions.
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Recommender Systems Complete Course Beginner to Advanced - Project 1: Song Recommendation System Using Content-Based Filtering: Fuzzywuzzy Implementation
You will learn to develop the two types of functions needed to make the recommender engine.
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Recommender Systems Complete Course Beginner to Advanced - Project 1: Song Recommendation System Using Content-Based Filtering: Similarity Index
In this lesson, we will explore how to use the similarity index.
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Recommender Systems Complete Course Beginner to Advanced - Project 1: Song Recommendation System Using Content-Based Filtering: tf-idf Implementation
In this video, we will understand how to calculate and use the tf-idf vectorizers with sklearn.
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Recommender Systems Complete Course Beginner to Advanced - Project 1: Song Recommendation System Using Content-Based Filtering: Occurrence Count
In this video, you will learn how to count the number of occurrences of each element in content-based filtering.
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Recommender Systems Complete Course Beginner to Advanced - Project 1: Song Recommendation System Using Content-Based Filtering: Exploring Genres
In this lesson, we will explore the elements of the dataset called genres.