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Machine Learning: Random Forest with Python from Scratch - Pros and Cons of Random Forest
In this video, we will look at the benefits and limitations of Random Forest and the complexities involved in decision-making using Random Forest. This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine...
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Machine Learning: Random Forest with Python from Scratch - Overfitting and Underfitting
In this video, you will learn about overfitting, a modeling error when a model performs well in training but not in testing, and underfitting, where the model neither performs well during training nor during testing. This clip is from...
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Fundamentals of Neural Networks - Residual Network
Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously. This clip is from the chapter "Convolutional Neural...
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Recommender Systems Complete Course Beginner to Advanced - Project 1: Song Recommendation System Using Content-Based Filtering: Dataset Usage
In this lesson, you will learn to develop our content-based filtering for the song project.
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Recommender Systems Complete Course Beginner to Advanced - Project 1: Song Recommendation System Using Content-Based Filtering: Project Introduction
This video provides a brief overview of the content-based recommender system for songs.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Quiz Solution
This video is the solution to the quiz based on the learnings of the lectures and concepts so far.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Quiz
This video is a quiz based on the learnings of the lectures and concepts so far.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: User-Based Collaborative Filtering
In this lesson, we will discuss user-based collaborative filtering in machine learning for a recommender system.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: KNN Implementation
In this lesson, you will learn how to implement the k-nearest neighbor algorithm in machine learning.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Geographic Filtering
In this lesson, you will learn how to filter users in a recommendation system based on a geographical region.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Collaborative Filtering using KNN
This video demonstrates implementing a collaborative filter using the k-nearest neighbor algorithm.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Age Distribution for Users
In this video, we will develop a histogram to visualize the age distribution for users.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Item-Based Filtering Data Preparation
In this video, you will learn to implement Python to develop item-based collaborative filtering using Pandas, NumPy, and Matplotlib.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Item-Based Collaborative Filtering
In this video, you will learn to use machine learning to develop item-based collaborative filtering.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Making Recommendations
In this video, we will understand how to make a recommendation after creating the recommendation engine.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Recommendation Engine
In this lesson, we will begin making the recommendation engine and train the model to make recommendations.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: tf-idf Matrix
In this video, you will learn to make the recommendation engine using the tf-idf matrix.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Exploring Genres in Content-Based Filtering
After learning to explore genres, we will look at term frequency and inverse document frequency.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Data Manipulation for Content-Based Filtering
In this lesson, you will learn how to extract information from our dataset.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Data Preparation for Content-Based Filtering
In this lesson, you will learn to develop content-based filtering for a recommender system using Python.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Design Approaches for ML
In this lecture, we will explore the design approaches for recommender systems using machine learning.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Guidelines for ML
In this video, we will discuss a few guidelines for machine learning-based recommender systems.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Benefits of Machine Learning
Let's understand what role machine learning plays in a recommender system and what are the benefits of machine learning.
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Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Overview
This video provides a brief outline of machine learning in recommender systems and how machine learning helps us adopt multiple types of recommender systems.