Udemy - Practical Recommender Systems For Business Applications in R

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size2 GB
  • Uploaded Byfreecoursewb
  • Downloads24
  • Last checkedMay. 08th '22
  • Date uploadedMay. 06th '22
  • Seeders 3
  • Leechers8

Infohash : 127F4B9C77447D1F9E1D1AF910770C526B9F4DDB

Practical Recommender Systems For Business Applications in R



https://DevCourseWeb.com

Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.90 GB | Duration: 36 lectures • 3h 19m

Implementing Data Science Driven Recommender Systems For Business Applications With R

What you'll learn
Learn what recommender systems are and their importance for business intelligence
Learn the main aspects of implementing data science technique within the R Programming Language
Implement practical recommender systems using R Programming Language
Learn about the theoretical and practical aspects of recommender systems

Requirements
Be Able To Operate & Install Software On A Computer
Prior Exposure to R Programming Concepts Will be Helpful
Prior Exposure to the R Studio Environment
An Interest in Learning About Practical Recommender Systems
Description
ENROLL IN MY LATEST COURSE ON HOW TO LEARN ALL ABOUT BUILDING PRACTICAL RECOMMENDER SYSTEMS WITH R

Files:

[ DevCourseWeb.com ] Udemy - Practical Recommender Systems For Business Applications in R
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 01 - Welcome to the Course
    • 001 What Is the Course About.mp4 (36.3 MB)
    • 001 What Is the Course About_en.vtt (2.7 KB)
    • 002 Data and Code.html (0.1 KB)
    • 003 Install R and RStudio.mp4 (64.5 MB)
    • 003 Install R and RStudio_en.vtt (6.4 KB)
    • 004 Different Data Types.mp4 (46.2 MB)
    • 004 Different Data Types_en.vtt (3.8 KB)
    • 005 Why Recommender Systems.mp4 (48.8 MB)
    • 005 Why Recommender Systems_en.vtt (4.4 KB)
      • __MACOSX data_code Section2
      • _Lecture10_more dta clean.txt (0.3 KB)
      • _Lecture11_pipeop.txt (0.7 KB)
      • _Lecture12_dplyr_part1.txt (0.3 KB)
      • _Lecture13_dplyr_part2.txt (0.3 KB)
      • _Lecture14_joining_inner.txt (0.5 KB)
      • _Lecture15_jwidelong.txt (0.4 KB)
      • _Lecture16_ratings.txt (0.5 KB)
      • _Lecture6_csv-excel.txt (0.3 KB)
      • _Lecture7_readHTML_xml.txt (0.3 KB)
      • _Lecture8_readHTML_rcurl.txt (0.3 KB)
      • _Lecture9_dta_r.txt (0.7 KB)
      • _Resp1.csv (0.3 KB)
      • _countries_ecologicalF.csv (0.3 KB)
      • _winequality-red.csv (0.3 KB)
      Section3
      • _cosine.txt (0.4 KB)
      • _svdr.txt (0.4 KB)
      Section4
      • _cluster_1.txt (0.5 KB)
      • _cosine_recommend.txt (0.4 KB)
      • _item_rec.txt (0.5 KB)
      • _jesterfinal151cols.csv (0.2 KB)
      • _recommenderlab.txt (0.4 KB)
      • _recommenderlab_cosine.txt (0.5 KB)
      • _recommenderlab_prac.txt (0.5 KB)
        • books
        • _BX-Users.csv (0.2 KB)
        data_code
        • Rhistory (13.8 KB)
          • Section2
          • Lecture10_more dta clean.txt (0.9 KB)
          • Lecture11_pipeop.txt (0.9 KB)
          • Lecture12_dplyr_part1.txt (0.8 KB)
          • Lecture13_dplyr_part2.txt (0.8 KB)
          • Lecture14_joining_inner.txt (0.4 KB)
          • Lecture15_jwidelong.txt (0.9 KB)
          • Lecture16_ratings.txt (0.5 KB)
          • Lecture6_csv-excel.txt (0.6 KB)
          • Lecture7_readHTML_xml.txt (0.5 KB)
          • Lecture8_readHTML_rcurl.txt (0.8 KB)
          • Lecture9_dta_r.txt (0.1 KB)
          • Resp1.csv (0.3 KB)
          • _Lecture10_more dta clean.txt (4.0 KB)
          • _Lecture11_pipeop.txt (4.0 KB)
          • _Lecture12_dplyr_part1.txt (4.0 KB)
          • _Lecture13_dplyr_part2.txt (4.0 KB)
          • _Lecture14_joining_inner.txt (4.0 KB)
          • _Lecture15_jwidelong.txt (4.0 KB)
          • _Lecture16_ratings.txt (4.0 KB)
          • _Lecture6_csv-excel.txt (4.0 KB)
          • _Lecture7_readHTML_xml.txt (4.0 KB)
          • _Lecture8_readHTML_rcurl.txt (4.0 KB)
          • _Lecture9_dta_r.txt (4.0 KB)
          • _Resp1.csv (4.0 KB)
          • _countries_ecologicalF.csv (4.0 KB)
          • _winequality-red.csv (4.0 KB)
          • countries_ecologicalF.csv (22.0 KB)
          • winequality-red.csv (82.2 KB)
          Section3
          • _cosine.txt (4.0 KB)
          • _svdr.txt (4.0 KB)
          • cosine.txt (0.2 KB)
          • svdr.txt (1.3 KB)
          Section4
          • _cluster_1.txt (4.0 KB)
          • _cosine_recommend.txt (4.0 KB)
          • _item_rec.txt (4.0 KB)
          • _jesterfinal151cols.csv (4.0 KB)
          • _recommenderlab.txt (4.0 KB)
          • _recommenderlab_cosine.txt (4.0 KB)
          • _recommenderlab_prac.txt (4.0 KB)
            • books
            • BX-Book-Ratings.csv (29.3 MB)
            • BX-Books.csv (74.2 MB)
            • BX-Users.csv (11.7 MB)
            • _BX-Users.csv (4.0 KB)
          • cluster_1.txt (1.0 KB)
          • cosine_recommend.txt (1.9 KB)
          • item_rec.txt (2.9 KB)
          • jesterfinal151cols.csv (29.0 MB)
          • recommenderlab.txt (0.4 KB)
          • recommenderlab_cosine.txt (2.5 KB)
          • recommenderlab_prac.txt (3.7 KB)
            • 02 - Basic R Programming
            • 001 Read CSV and Excel Data.mp4 (111.4 MB)
            • 001 Read CSV and Excel Data_en.vtt (10.6 KB)
            • 002 Read in Data from Online HTML Tables-Part 1.mp4 (56.5 MB)
            • 002 Read in Data from Online HTML Tables-Part 1_en.vtt (4.1 KB)
            • 003 Read in Data from Online HTML Tables-Part 2.mp4 (83.5 MB)
            • 003 Read in Data from Online HTML Tables-Part 2_en.vtt (6.8 KB)
            • 004 Data Cleaning.mp4 (134.5 MB)
            • 004 Data Cleaning_en.vtt (16.4 KB)
            • 005 More Data Cleaning.mp4 (82.7 MB)
            • 005 More Data Cleaning_en.vtt (8.5 KB)
            • 006 Pre-processing Tasks and the Pipe Operator.mp4 (91.9 MB)
            • 006 Pre-processing Tasks and the Pipe Operator_en.vtt (8.3 KB)
            • 007 DPLYR-1.mp4 (81.8 MB)
            • 007 DPLYR-1_en.vtt (6.0 KB)
            • 008 DPLYR-2.mp4 (42.5 MB)
            • 008 DPLYR-2_en.vtt (4.9 KB)
            • 009 Some Joining.mp4 (81.5 MB)
            • 009 Some Joining_en.vtt (6.0 KB)
            • 010 The Tall and Short Of It.mp4 (25.6 MB)
            • 010 The Tall and Short Of It_en.vtt (2.1 KB)
            • 011 Visualize Ratings.mp4 (42.7 MB)
            • 011 Visualize Ratings_en.vtt (2.9 KB)
            03 - Basic Statistical Concepts Underpinning Recommender Systems
            • 001 Principal Components Analysis (PCA)-Theory.mp4 (24.4 MB)
            • 001 Principal Components Analysis (PCA)-Theory_en.vtt (3.0 KB)
            • 002 Implement PCA in R.mp4 (112.6 MB)
            • 002 Implement PCA in R_en.vtt (13.1 KB)
            • 003 Single Vector Decomposition (SVD)- Theory.mp4 (8.4 MB)
            • 003 Single Vector Decomposition (SVD)- Theory_en.vtt (1.5 KB)
            • 004 Imp

Code:

  • udp://tracker.torrent.eu.org:451/announce
  • udp://tracker.tiny-vps.com:6969/announce
  • http://tracker.foreverpirates.co:80/announce
  • udp://tracker.cyberia.is:6969/announce
  • udp://exodus.desync.com:6969/announce
  • udp://explodie.org:6969/announce
  • udp://tracker.opentrackr.org:1337/announce
  • udp://9.rarbg.to:2780/announce
  • udp://tracker.internetwarriors.net:1337/announce
  • udp://ipv4.tracker.harry.lu:80/announce
  • udp://open.stealth.si:80/announce
  • udp://9.rarbg.to:2900/announce
  • udp://9.rarbg.me:2720/announce
  • udp://opentor.org:2710/announce