[ DevCourseWeb.com ] Udemy - Recommendation system Real World Projects using Python

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[ DevCourseWeb.com ] Udemy - Recommendation system Real World Projects using Python

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种子哈希：1fd96c4fc170ab693d6146a82c27f2e568b34c34
文件大小： 2.08G
已经下载：1510次
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收录时间：2022-01-15
最近下载：2025-07-22

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文件列表

  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/008 Lets Build Content_based model.mp4 140.5 MB
  • ~Get Your Files Here !/03 - Build a Recommendation System using Average Weighted/004 Lets Recommend movies using Average_weighted_Technique.mp4 120.7 MB
  • ~Get Your Files Here !/09 - Build a Recommender System using Co-rrelation/004 Lets Build recommender system using Co-relation.mp4 112.7 MB
  • ~Get Your Files Here !/10 - Build a Recommender System using KNN-based Collaborative filtering/002 Lets Build KNN based collabarative model.mp4 105.1 MB
  • ~Get Your Files Here !/09 - Build a Recommender System using Co-rrelation/001 Lets Perform Data Preparation.mp4 102.7 MB
  • ~Get Your Files Here !/07 - Build a more Advance recommendation system using Content based filtering/004 What is Meta-data & how to Create meta-data.mp4 102.0 MB
  • ~Get Your Files Here !/03 - Build a Recommendation System using Average Weighted/002 Lets Prepare data for analysis & Model building.mp4 99.5 MB
  • ~Get Your Files Here !/03 - Build a Recommendation System using Average Weighted/003 Getting Overview of Average_weighted_Technique.mp4 96.6 MB
  • ~Get Your Files Here !/04 - Build a recommendation system using Popularity Score/001 Lets Implement Popularity based Recommender System.mp4 95.2 MB
  • ~Get Your Files Here !/07 - Build a more Advance recommendation system using Content based filtering/003 Lets clean & prepare our data.mp4 92.2 MB
  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/005 Applying TF-IDF on our data _.mp4 87.4 MB
  • ~Get Your Files Here !/09 - Build a Recommender System using Co-rrelation/002 Applying Statistical Approaches on Data _.mp4 84.2 MB
  • ~Get Your Files Here !/05 - Build a recommendation system using Weighted average and Popularity score/002 Lets recommend movies using Hybrid model.mp4 74.3 MB
  • ~Get Your Files Here !/05 - Build a recommendation system using Weighted average and Popularity score/001 How to Normalize your Data _.mp4 72.1 MB
  • ~Get Your Files Here !/09 - Build a Recommender System using Co-rrelation/003 What is Pivot_Table & how to create it _.mp4 68.8 MB
  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/001 Lets Understand about Content Based Recommendation system.mp4 67.9 MB
  • ~Get Your Files Here !/07 - Build a more Advance recommendation system using Content based filtering/002 Lets perform Feature Extraction _.mp4 66.1 MB
  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/002 Intuition Behind Bag of Words - Part 1.mp4 65.6 MB
  • ~Get Your Files Here !/10 - Build a Recommender System using KNN-based Collaborative filtering/001 Lets explore our data.mp4 65.0 MB
  • ~Get Your Files Here !/07 - Build a more Advance recommendation system using Content based filtering/001 Understand how to improve Model from business perspective _.mp4 60.9 MB
  • ~Get Your Files Here !/10 - Build a Recommender System using KNN-based Collaborative filtering/003 How to make your Recommendations more Interactive _.mp4 56.6 MB
  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/006 Applying Sigmoid kernel on data _.mp4 52.9 MB
  • ~Get Your Files Here !/03 - Build a Recommendation System using Average Weighted/001 Getting a High-level Overview of data.mp4 52.4 MB
  • ~Get Your Files Here !/01 - Introduction & welcome to this course _/005 Introduction to Jupyter Notebook _.mp4 45.5 MB
  • ~Get Your Files Here !/07 - Build a more Advance recommendation system using Content based filtering/005 Lets Recommend Movies.mp4 45.5 MB
  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/007 How to design a function from scratch in real-world _.mp4 43.9 MB
  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/004 Intuition Behind Tf-IDF - Part 2.mp4 36.3 MB
  • ~Get Your Files Here !/01 - Introduction & welcome to this course _/001 Introduction to course & its benefits _.mp4 29.2 MB
  • ~Get Your Files Here !/01 - Introduction & welcome to this course _/003 How to follow this course , must watch _.mp4 28.0 MB
  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/003 Intuition Behind TF_IDF Part 1.mp4 26.0 MB
  • ~Get Your Files Here !/01 - Introduction & welcome to this course _/004 Pre-requisites (Anaconda Python & Jupter install & Set-up).mp4 25.6 MB
  • ~Get Your Files Here !/01 - Introduction & welcome to this course _/002 Utilize QnA section ( Golden Oppurtunity ) _.mp4 9.8 MB
  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/008 Lets Build Content_based model_en.vtt 19.3 kB
  • ~Get Your Files Here !/09 - Build a Recommender System using Co-rrelation/001 Lets Perform Data Preparation_en.vtt 17.7 kB
  • ~Get Your Files Here !/03 - Build a Recommendation System using Average Weighted/004 Lets Recommend movies using Average_weighted_Technique_en.vtt 17.1 kB
  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/002 Intuition Behind Bag of Words - Part 1_en.vtt 16.8 kB
  • ~Get Your Files Here !/09 - Build a Recommender System using Co-rrelation/004 Lets Build recommender system using Co-relation_en.vtt 15.4 kB
  • ~Get Your Files Here !/03 - Build a Recommendation System using Average Weighted/003 Getting Overview of Average_weighted_Technique_en.vtt 14.7 kB
  • ~Get Your Files Here !/10 - Build a Recommender System using KNN-based Collaborative filtering/002 Lets Build KNN based collabarative model_en.vtt 14.6 kB
  • ~Get Your Files Here !/07 - Build a more Advance recommendation system using Content based filtering/003 Lets clean & prepare our data_en.vtt 13.6 kB
  • ~Get Your Files Here !/03 - Build a Recommendation System using Average Weighted/002 Lets Prepare data for analysis & Model building_en.vtt 13.2 kB
  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/005 Applying TF-IDF on our data __en.vtt 12.8 kB
  • ~Get Your Files Here !/07 - Build a more Advance recommendation system using Content based filtering/004 What is Meta-data & how to Create meta-data_en.vtt 12.8 kB
  • ~Get Your Files Here !/09 - Build a Recommender System using Co-rrelation/002 Applying Statistical Approaches on Data __en.vtt 12.6 kB
  • ~Get Your Files Here !/04 - Build a recommendation system using Popularity Score/001 Lets Implement Popularity based Recommender System_en.vtt 12.1 kB
  • ~Get Your Files Here !/05 - Build a recommendation system using Weighted average and Popularity score/001 How to Normalize your Data __en.vtt 10.8 kB
  • ~Get Your Files Here !/05 - Build a recommendation system using Weighted average and Popularity score/002 Lets recommend movies using Hybrid model_en.vtt 10.4 kB
  • ~Get Your Files Here !/09 - Build a Recommender System using Co-rrelation/003 What is Pivot_Table & how to create it __en.vtt 10.1 kB
  • ~Get Your Files Here !/10 - Build a Recommender System using KNN-based Collaborative filtering/001 Lets explore our data_en.vtt 9.8 kB
  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/001 Lets Understand about Content Based Recommendation system_en.vtt 9.5 kB
  • ~Get Your Files Here !/03 - Build a Recommendation System using Average Weighted/001 Getting a High-level Overview of data_en.vtt 9.0 kB
  • ~Get Your Files Here !/07 - Build a more Advance recommendation system using Content based filtering/002 Lets perform Feature Extraction __en.vtt 8.9 kB
  • ~Get Your Files Here !/07 - Build a more Advance recommendation system using Content based filtering/001 Understand how to improve Model from business perspective __en.vtt 7.8 kB
  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/003 Intuition Behind TF_IDF Part 1_en.vtt 7.7 kB
  • ~Get Your Files Here !/10 - Build a Recommender System using KNN-based Collaborative filtering/003 How to make your Recommendations more Interactive __en.vtt 7.6 kB
  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/004 Intuition Behind Tf-IDF - Part 2_en.vtt 7.4 kB
  • ~Get Your Files Here !/01 - Introduction & welcome to this course _/005 Introduction to Jupyter Notebook __en.vtt 7.3 kB
  • ~Get Your Files Here !/07 - Build a more Advance recommendation system using Content based filtering/005 Lets Recommend Movies_en.vtt 6.6 kB
  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/006 Applying Sigmoid kernel on data __en.vtt 6.5 kB
  • ~Get Your Files Here !/06 - Build a recommendation system using Content based filtering/007 How to design a function from scratch in real-world __en.vtt 6.1 kB
  • ~Get Your Files Here !/01 - Introduction & welcome to this course _/001 Introduction to course & its benefits __en.vtt 6.1 kB
  • ~Get Your Files Here !/01 - Introduction & welcome to this course _/003 How to follow this course , must watch __en.vtt 5.0 kB
  • ~Get Your Files Here !/01 - Introduction & welcome to this course _/004 Pre-requisites (Anaconda Python & Jupter install & Set-up)_en.vtt 4.4 kB
  • ~Get Your Files Here !/01 - Introduction & welcome to this course _/002 Utilize QnA section ( Golden Oppurtunity ) __en.vtt 2.4 kB
  • ~Get Your Files Here !/Bonus Resources.txt 386 Bytes
  • ~Get Your Files Here !/02 - ------------------- Project 1 _ TMDB use-case ----------------------/001 Datasets & Resources.html 193 Bytes
  • ~Get Your Files Here !/08 - ------------------- Project 2 _ Movie_lens use-case --------------------/002 Datasets & Resources.html 193 Bytes
  • Get Bonus Downloads Here.url 182 Bytes
  • ~Get Your Files Here !/08 - ------------------- Project 2 _ Movie_lens use-case --------------------/001 intro.html 53 Bytes

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