SciShow
Does Depression Make You More Realistic?
Popular culture has occasionally touched on the idea that people with depression are more objective judges of the world around them, but research has shown that’s not necessarily true.
TED Talks
Annette Heuser: The 3 agencies with the power to make or break economies
The way we rate national economies is all wrong, says rating agency reformer Annette Heuser. With mysterious and obscure methods, three private US-based credit rating agencies wield immense power over national economies across the globe,...
TED Talks
TED: Where is cybercrime really coming from? | Caleb Barlow
Cybercrime netted a whopping $450 billion in profits last year, with 2 billion records lost or stolen worldwide. Security expert Caleb Barlow calls out the insufficiency of our current strategies to protect our data. His solution? We...
Curated Video
Ecommerce Customer Retention Strategy
Dive into the world of ecommerce customer retention strategy in this insightful video. Discover the techniques and tactics to foster lasting relationships with your customers. Explore loyalty programs, personalized experiences,...
Curated Video
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.
Curated Video
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.
Curated Video
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.
Curated Video
Recommender Systems Complete Course Beginner to Advanced - Basics of Recommender System: Collaborative Filtering and User-Based Collaborative Filtering
In this lesson, you will learn about collaborative filtering and user-based collaborative filtering.
Curated Video
Recommender Systems Complete Course Beginner to Advanced - Basics of Recommender System: Error Metric Computation
In this video, we will look at some of the metrics used to measure a recommender system's quality.
Curated Video
Recommender Systems Complete Course Beginner to Advanced - Basics of Recommender System: Data Partitioning
Here, we will look at data partitioning, represented as a URL.
Curated Video
Recommender Systems Complete Course Beginner to Advanced - Basics of Recommender System: Offline Evaluation Techniques
In this video, you will learn about the evaluation technique and focus on the offline evaluation technique in this lecture.
Curated Video
Recommender Systems Complete Course Beginner to Advanced - Basics of Recommender System: Quality of Recommender System
In this lesson, we will look at the quality of recommender systems through inferred preferences and ways to collect user opinions.
Curated Video
Recommender Systems Complete Course Beginner to Advanced - Basics of Recommender System: User Rating Matrix
In this video, we will understand what a user rating matrix is and how we can build a user rating matrix.
Curated Video
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.
Curated Video
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.
Curated Video
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.
Curated Video
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.
Curated Video
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.
Curated Video
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.
Curated Video
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.
Curated Video
React JS Masterclass - Go From Zero To Job Ready - Filter: Context and Reducers / 111
Let's understand UserContext Hook, which makes it easy to pass data throughout your app without manually passing props down the tree, and UseReducer Hook, which allows for a more straightforward, predictable, and organized way to update...
Curated Video
CompTIA A+ Certification Core 1 (220-1101) - Cables and Connectors
Networking uses many different types of cables such as coaxial, twisted pair, and even fiber-optic. These different cables use special connectors, and a good tech should recognize the different cables and their connectors. This clip is...
Curated Video
Recommender Systems with Machine Learning - Active Users and Popular Movies
This video explains the active users and popular movies available. This clip is from the chapter "Project 2: Movie Recommendation System Using Collaborative Filtering" of the series "Recommender Systems with Machine Learning".null
Curated Video
Recommender Systems with Machine Learning - Count
This video explains the count function. This clip is from the chapter "Project 2: Movie Recommendation System Using Collaborative Filtering" of the series "Recommender Systems with Machine Learning".null