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Recommender Systems Complete Course Beginner to Advanced - Project Amazon Product Recommendation System: Making Recommendations
We will now perform some recommendations using the brute-force algorithms and then perform the indexing of our data.
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Recommender Systems Complete Course Beginner to Advanced - Project Amazon Product Recommendation System: Accuracy Versus Recommendations
We will now perform data visualization; we will check the accuracy of our recommender model with the recommendations.
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Recommender Systems Complete Course Beginner to Advanced - Project Amazon Product Recommendation System: Compute Loss
This is the next step of training our model, which entails the compute loss model.
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Recommender Systems Complete Course Beginner to Advanced - Project Amazon Product Recommendation System: Candidate Tower and Retrieval System
In this lesson, we will look at making the candidate tower and then execute a retrieval system.
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Recommender Systems Complete Course Beginner to Advanced - Project Amazon Product Recommendation System: Making the Model and Query Tower
After testing and training the recommendations, we will develop the model by loading the Tensor board extension.
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Recommender Systems Complete Course Beginner to Advanced - Project Amazon Product Recommendation System: Random Train-Test Split
After mapping the rating to the dataset, we will train-test split the dataset to our recommender system with shuffling and prediction.
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Recommender Systems Complete Course Beginner to Advanced - Project Amazon Product Recommendation System: Rating Our Data
Let us now move to the next part of the project, including the rating of our data with a new mapping dictionary.
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Recommender Systems Complete Course Beginner to Advanced - Project Amazon Product Recommendation System: Make Tensors from DataFrame
We will now advance further by checking our dataset using a single user and developing the Tensor from DataFrame.
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Recommender Systems Complete Course Beginner to Advanced - Project Amazon Product Recommendation System: Data Visualization with WordCloud
In this video, we will explore how to load the dataset and begin data visualization using WordCloud.
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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: 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 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: 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.
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Recommender Systems Complete Course Beginner to Advanced - Project 1: Song Recommendation System Using Content-Based Filtering: Missing Values
In this lesson, we will develop a new data frame for our content-based filtering for missing values.
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SwiftUI and Node.js Full Stack - Build Twitter - iOS 16 - Switch Statement
This video explains the Switch statement.
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SwiftUI and Node.js Full Stack - Build Twitter - iOS 16 - Basic Operators and If Statements
This video explains basic operators and If statements.
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SwiftUI and Node.js Full Stack - Build Twitter - iOS 16 - Notification Display
In this video, you will learn how to display notifications in our Twitter Clone app.
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SwiftUI and Node.js Full Stack - Build Twitter - iOS 16 - Notification Functions
In this video, we will be creating notification functions for our full-stack Twitter Clone app. These functions will allow us to send notifications to users when certain events occur, such as when someone follows them or likes their tweet.