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[FreeCourseSite.com] Udemy - Recommendation Engine Bootcamp with 3 Capstone Projects

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种子名称: [FreeCourseSite.com] Udemy - Recommendation Engine Bootcamp with 3 Capstone Projects
文件类型: 视频
文件数目: 58个文件
文件大小: 2.76 GB
收录时间: 2021-7-24 10:00
已经下载: 3
资源热度: 148
最近下载: 2024-6-2 18:40

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[FreeCourseSite.com] Udemy - Recommendation Engine Bootcamp with 3 Capstone Projects.torrent
  • 01 Introduction to Recommendation System/001 Introduction to Recommender systems.mp440.52MB
  • 01 Introduction to Recommendation System/002 What are it's Use Cases.mp445.12MB
  • 01 Introduction to Recommendation System/003 Types of Recommender Systems.mp456.69MB
  • 01 Introduction to Recommendation System/004 Evaluating Recommender Systems.mp453.12MB
  • 01 Introduction to Recommendation System/005 Q and A.mp431.99MB
  • 02 Content Based Filtering/001 Introduction to Content Based Filtering.mp458.94MB
  • 02 Content Based Filtering/002 Preprocessing the Data for Content Based Filtering.mp476.66MB
  • 02 Content Based Filtering/003 Filtering Movies Based on Genres.mp458.72MB
  • 02 Content Based Filtering/004 Introduction to Transactional Encoder.mp463.35MB
  • 02 Content Based Filtering/005 Recommending Similar Movies to Watch.mp456.03MB
  • 02 Content Based Filtering/006 Quiz Solution.mp448.54MB
  • 03 Collaborative Based Filtering/001 Introduction to Collaborative Filtering.mp480.84MB
  • 03 Collaborative Based Filtering/002 Preprocessing the Data for Collaborative Filtering.mp472.39MB
  • 03 Collaborative Based Filtering/003 Implementation of User Based Collaborative Filtering.mp462.1MB
  • 03 Collaborative Based Filtering/004 Interpreting the Results obtained from User Based Filtering.mp463.59MB
  • 03 Collaborative Based Filtering/005 Implementation of Item Based Collaborative Filtering.mp463.55MB
  • 03 Collaborative Based Filtering/006 Quiz Solution.mp455.66MB
  • 04 Singular Value Decomposition/001 Introduction to SVD.mp4111.94MB
  • 04 Singular Value Decomposition/002 Implementing SVD using Surprise.mp440.67MB
  • 04 Singular Value Decomposition/003 Interpreting Results Obtained from SVD.mp445.99MB
  • 04 Singular Value Decomposition/004 Comparing Content, and Collaborative Based Filtering.mp462.04MB
  • 04 Singular Value Decomposition/005 Quiz Solution.mp447.94MB
  • 05 Case Studies from Giants/001 Case Study for Netflix.mp456.36MB
  • 05 Case Studies from Giants/002 Case Study for Youtube.mp458.14MB
  • 06 Movie Recommender Systems/001 Setting up the Environment.mp445.52MB
  • 06 Movie Recommender Systems/002 Taking a Deep Dive into the Dataset.mp448.43MB
  • 06 Movie Recommender Systems/003 Understanding the Problem Statement.mp430.68MB
  • 06 Movie Recommender Systems/004 Missing Values Imputation.mp451.87MB
  • 06 Movie Recommender Systems/005 Top 10 Profitable Movies.mp450.06MB
  • 06 Movie Recommender Systems/006 Manipulating the Duration and Language Column.mp451.35MB
  • 06 Movie Recommender Systems/007 Extracting the Movie Genres.mp449.77MB
  • 06 Movie Recommender Systems/008 Top 10 Most Popular Movies on Social Media.mp432.7MB
  • 06 Movie Recommender Systems/009 Analyzing Which Genre is Most Bankable_.mp438.35MB
  • 06 Movie Recommender Systems/010 Loss and Profit Analysis on English and Foreign Movies.mp442.2MB
  • 06 Movie Recommender Systems/011 Gross Comparison of Long and Short Movies.mp446.15MB
  • 06 Movie Recommender Systems/012 Association between IMDB Rating and Duration.mp447.29MB
  • 06 Movie Recommender Systems/013 Comparing Critically acclaimed Actors.mp460.55MB
  • 06 Movie Recommender Systems/014 Top Movies based on Gross, and IMDB.mp433.47MB
  • 06 Movie Recommender Systems/015 Recommending Movies based on Languages and Actors.mp446.8MB
  • 06 Movie Recommender Systems/016 Recommending Similar Genres and Movies.mp468.34MB
  • 06 Movie Recommender Systems/017 Key Takeaways from this Project.mp433.39MB
  • 07 Open Jobs Analyzer and Recommendation System/001 Understanding the Problem Statement.mp439.21MB
  • 07 Open Jobs Analyzer and Recommendation System/002 Setting up the Environment.mp461.4MB
  • 07 Open Jobs Analyzer and Recommendation System/003 Taking a Deep Dive into the Job Dataset.mp438.56MB
  • 07 Open Jobs Analyzer and Recommendation System/004 Analyzing the Job Metrices.mp424.8MB
  • 07 Open Jobs Analyzer and Recommendation System/005 Finding Important Metrics for Salary.mp457.71MB
  • 07 Open Jobs Analyzer and Recommendation System/006 Taking a Deep Dive at the Naukri Dataset.mp427.88MB
  • 07 Open Jobs Analyzer and Recommendation System/007 Finding Locations with Highest Job Vacancies.mp453.89MB
  • 07 Open Jobs Analyzer and Recommendation System/008 Analyzing the Experience required for Jobs.mp425.87MB
  • 07 Open Jobs Analyzer and Recommendation System/009 Most Demanded Degrees for Jobs.mp427.3MB
  • 07 Open Jobs Analyzer and Recommendation System/010 Analyzing the Industries with highest no. of Jobs.mp432.13MB
  • 07 Open Jobs Analyzer and Recommendation System/011 Analyzing the Top Skills required for Jobs.mp433.96MB
  • 07 Open Jobs Analyzer and Recommendation System/012 Cleaning the Rest of the Dataset.mp436.71MB
  • 07 Open Jobs Analyzer and Recommendation System/013 Gathering Vital Information from the Dataset.mp427.15MB
  • 07 Open Jobs Analyzer and Recommendation System/014 Making a Function to Search for Jobs.mp433.29MB
  • 07 Open Jobs Analyzer and Recommendation System/015 Understanding Relation between Industries and Education.mp435.19MB
  • 07 Open Jobs Analyzer and Recommendation System/016 Key Takeaways and Findings from the Project.mp434.08MB
  • 08 Outro Section/001 Conclusion.mp446.28MB