种子简介

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次
资源热度： 189
最近下载： 2024-11-12 08:36

下载BT种子文件

下载Torrent文件(.torrent) 立即下载

磁力链接下载

magnet:?xt=urn:btih:10fbe60b2e124aab6465d9b6d8eba2c9b00eeafb&dn=[FreeCourseSite.com] Udemy - Recommendation Engine Bootcamp with 3 Capstone Projects 复制链接到迅雷、QQ旋风进行下载，或者使用百度云离线下载。

喜欢这个种子的人也喜欢

种子包含的文件

[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