Curated Video
Recommender Systems with Machine Learning - Dataset Discussion
This video involves a deep understanding of the dataset to be explored for this module. This clip is from the chapter "Project 2: Movie Recommendation System Using Collaborative Filtering" of the series "Recommender Systems with Machine...
Curated Video
Recommender Systems with Machine Learning - Project Introduction-2
This video provides an introduction to the project. 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 - Find the st Title
This video explains how to find the closest title from the dataset as per the input. This clip is from the chapter "Project 1: Song Recommendation System Using Content-Based Filtering" of the series "Recommender Systems with Machine...
Curated Video
Recommender Systems with Machine Learning - FuzzyWuzzy Implementation
This video helps you with the implementation of the FuzzyWuzzy algorithm. This clip is from the chapter "Project 1: Song Recommendation System Using Content-Based Filtering" of the series "Recommender Systems with Machine Learning".This...
Curated Video
Recommender Systems with Machine Learning - Similarity Index
This video talks about the similarity index in detail. This clip is from the chapter "Project 1: Song Recommendation System Using Content-Based Filtering" of the series "Recommender Systems with Machine Learning".This section focuses on...
Curated Video
Recommender Systems with Machine Learning - tf-idf (Term Frequency-Inverse Document Frequency) Implementation
This video demonstrates the implementation of tf-idf (Term Frequency-Inverse Document Frequency). This clip is from the chapter "Project 1: Song Recommendation System Using Content-Based Filtering" of the series "Recommender Systems with...
Curated Video
Recommender Systems with Machine Learning - Dataset Usage
This video explains how to use the dataset to your advantage. This clip is from the chapter "Project 1: Song Recommendation System Using Content-Based Filtering" of the series "Recommender Systems with Machine Learning".This section...
Curated Video
Recommender Systems with Machine Learning - Project Introduction-1
This video gives you an overview of the project. This clip is from the chapter "Project 1: Song Recommendation System Using Content-Based Filtering" of the series "Recommender Systems with Machine Learning".This section focuses on your...
Curated Video
Recommender Systems with Machine Learning - User-Based Collaborative Filtering
This video helps you with user-based collaborative filtering. This clip is from the chapter "Machine Learning for Recommender System" of the series "Recommender Systems with Machine Learning".This section focuses on the use of machine...
Curated Video
Recommender Systems with Machine Learning - Item-Based Collaborative Filtering
This video demonstrates item-based collaborative filtering. This clip is from the chapter "Machine Learning for Recommender System" of the series "Recommender Systems with Machine Learning".This section focuses on the use of machine...
Curated Video
Recommender Systems with Machine Learning - Data Preparation for Content-Based Filtering
This video explains data preparation for content-based filtering with machine learning. This clip is from the chapter "Machine Learning for Recommender System" of the series "Recommender Systems with Machine Learning".This section...
Curated Video
Recommender Systems with Machine Learning - Content-Based Filtering-2
This video helps you with content-based filtering. This clip is from the chapter "Machine Learning for Recommender System" of the series "Recommender Systems with Machine Learning".This section focuses on the use of machine learning for...
Curated Video
Recommender Systems with Machine Learning - Project Overview
This video discusses the projects you will be working on in the later sections of this course. This clip is from the chapter "Introduction" of the series "Recommender Systems with Machine Learning".This section provides an introduction...
Curated Video
Recommender Systems with Machine Learning - Fundamentals of Recommender Systems
This video helps you out with the fundamentals of recommender systems. This clip is from the chapter "Introduction" of the series "Recommender Systems with Machine Learning".This section provides an introduction to the course.
Curated Video
Linux Operating System: A Complete Linux Guide for Beginners - Additional Settings for VirtualBox
In this video, we will work on additional settings for VirtualBox. This clip is from the chapter "Download, Install, and Configure" of the series "Linux Operating System: A Complete Linux Guide for Beginners".In this section, we will...
Curated Video
Kafka for Developers - Data Contracts Using Schema Registry - Build the POST Endpoint for the CoffeeOrderService - /coffee_orders
In this video, we will build the POST endpoint in the controller, using which we can post new coffee orders. This clip is from the chapter "Build a Coffee Order Service Using Spring Boot and Schema Registry" of the series "Kafka for...
Curated Video
Kafka for Developers - Data Contracts Using Schema Registry - Add/Delete Optional Fields - FULL Compatibility
In this video, we will code and learn about FULL compatibility in Schema Registry. This clip is from the chapter "Data Evolution Using Schema Registry" of the series "Kafka for Developers - Data Contracts Using Schema Registry".In this...
Curated Video
Kafka for Developers - Data Contracts Using Schema Registry - Deleting a Field in Schema - BACKWARD Compatibility
In this video, we will code and learn about BACKWARD compatibility in Schema Registry. This clip is from the chapter "Data Evolution Using Schema Registry" of the series "Kafka for Developers - Data Contracts Using Schema Registry".In...
Curated Video
Kafka for Developers - Data Contracts Using Schema Registry - Update the Code to Interact with Maven Local Repository - Maven
In this video, we will code and learn about how to integrate our code to work with the Maven local repository. This clip is from the chapter "Data Evolution Using Schema Registry" of the series "Kafka for Developers - Data Contracts...
Curated Video
Kafka for Developers - Data Contracts Using Schema Registry - Date Logical Type
In this video, we will code and learn the date logical types. This clip is from the chapter "Logical Schema Types in AVRO" of the series "Kafka for Developers - Data Contracts Using Schema Registry".In this section, you will cover the...
Curated Video
Chatbots for Beginners: A Complete Guide to Build Chatbots - Deep Learning-Based Chatbot Architecture and Development: Tokenizer
You will learn to import the tokenizer with and without filters. We will fit the tokenizer into our vocabulary using the fit_on_texts built-in command. This clip is from the chapter "Advanced Chatbots with Deep Learning and Python" of...
Curated Video
Chatbots for Beginners: A Complete Guide to Build Chatbots - Deep Learning-Based Chatbot Architecture and Development: Develop Vocabulary
In this video, you will learn to combine the datasets, test data, and train data; we will use the all_data function to combine the datasets. This clip is from the chapter "Advanced Chatbots with Deep Learning and Python" of the series...
Curated Video
Chatbots for Beginners: A Complete Guide to Build Chatbots - Deep Learning-Based Chatbot Architecture and Development: Data Preparation
We will use the two datasets available for our project, the training QA and the testing QA. We will save them in our project folder and invoke them as needed. This clip is from the chapter "Advanced Chatbots with Deep Learning and...
Curated Video
Chatbots for Beginners: A Complete Guide to Build Chatbots - Deep Learning-Based Chatbot Architecture and Development: Steps Involved
In this lesson, you will learn about the various steps involved in developing chatbots based on deep learning techniques. We will install the required packages, define chat models and tokenization, and set up the encoder-decoder model....