Item based collaborative filtering in Python|Collaborative filtering in Python

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  • Опубликовано: 5 ноя 2024

Комментарии • 90

  • @wikasithaherath3119
    @wikasithaherath3119 3 года назад +2

    Good Job & great teaching .....really useful vedio ..Big thanks!

  • @sampuvedics
    @sampuvedics Год назад

    item based coolabartive filtering is wonderful.we also want user based collbrative foltering

  • @jadewang8173
    @jadewang8173 2 года назад +2

    sir, thank you for posting this video. I am working on an item-based cf recommender system with 60 million data for my dissertation. do you have any suggestion about what tools should I use (and learn quickly)? I feel like the data are too big for python. thanks in advance!

  • @SudhirKumar-vk6kn
    @SudhirKumar-vk6kn Год назад

    sir, thank you for uploading this video.
    sir, video and code of user-based collaborative filtering is not available on your tutorial, so kindly share the code and video or do you have any suggestion regarding this lecture ?

  • @anupajayakody458
    @anupajayakody458 Год назад

    Please publish a user based recommendation system video

  • @skydrows69
    @skydrows69 4 года назад +3

    hey, nice video !
    can you make a tutorial for user based collaborative filtering?

  • @priyankakomreddiwar8641
    @priyankakomreddiwar8641 3 года назад +1

    Hi.. Your video is really helpful.. Could u plz make a video on user based collaborative filtering?

    • @UnfoldDataScience
      @UnfoldDataScience  3 года назад

      Thanks Priyanka, that video is already in my channel. Let me know if you don't find.

    • @deurronni2417
      @deurronni2417 2 года назад

      @@UnfoldDataScience Hi, sorry! But I can't find the user based collaborative filtering in python. Can you give me the link, please?

  • @jugendrapalsingh5801
    @jugendrapalsingh5801 4 года назад +1

    very help full video

    • @UnfoldDataScience
      @UnfoldDataScience  4 года назад

      Thank you Jugendra.

    • @jugendrapalsingh5801
      @jugendrapalsingh5801 4 года назад

      @@UnfoldDataScience
      Dear sir Please
      Explain below question ...
      Question :
      The dataset provided contains movie reviews given by Amazon customers. Reviews were given between May 1996 and July 2014.
      Data Dictionary
      UserID - 4848 customers who provided a rating for each movie
      Movie 1 to Movie 206 - 206 movies for which ratings are provided by 4848 distinct users
      Data Considerations
      - All the users have not watched all the movies and therefore, all movies are not rated. These missing values are represented by NA.
      - Ratings are on a scale of -1 to 10 where -1 is the least rating and 10 is the best.
      Analysis Task
      - Exploratory Data Analysis:
      Which movies have maximum views/ratings?
      What is the average rating for each movie? Define the top 5 movies with the maximum ratings.
      Define the top 5 movies with the least audience.
      - Recommendation Model: Some of the movies hadn’t been watched and therefore, are not rated by the users. Netflix would like to take this as an opportunity and build a machine learning recommendation algorithm which provides the ratings for each of the users.
      Divide the data into training and test data
      Build a recommendation model on training data
      Make predictions on the test data

  • @ArpitYadav-ws5xe
    @ArpitYadav-ws5xe 3 года назад +1

    Excellent

    • @UnfoldDataScience
      @UnfoldDataScience  3 года назад

      Thanks Arpit.

    • @rucharaut3994
      @rucharaut3994 3 года назад

      @@UnfoldDataScience hello sir could you please make video on implementation of user base collaborative filtering?

  • @piyushtripathi6401
    @piyushtripathi6401 4 года назад +1

    very helping doc...share user based recommendation...

    • @UnfoldDataScience
      @UnfoldDataScience  4 года назад

      Thanks Piyush, will create the use based as well. Keep Learning!!

  • @raghavverma120
    @raghavverma120 2 года назад

    What’s the use of creating user-item matrix.. one can just find the movie similar to fargo using correlation.. and suggest the same to the users who like fargo

  • @gududurupradeepreddy6006
    @gududurupradeepreddy6006 2 года назад

    I have 1 doubt. May I know what are we recommending here? Why are we even considering and comparing the correlation with Fargo?

  • @rajat6937
    @rajat6937 4 года назад +2

    How companies gets data for their work they export datasets from database or directly use it to analyze data for ml works

    • @UnfoldDataScience
      @UnfoldDataScience  4 года назад +2

      Thats a good question Rajat, thanks for asking. Usually a connection is made to database and data is fetched for analysis. This is applicable if we have the needed data in Databases. If that is not the case we may need to fetch data from other places like Web, API etc

  • @cottoncandypinkandblue
    @cottoncandypinkandblue 2 года назад

    Thanks for this explanation. This really helps

  • @rog0079
    @rog0079 2 года назад

    Sir, thank you for this video, when is the user-based collaborative filtering python code tutorial video coming?

    • @UnfoldDataScience
      @UnfoldDataScience  2 года назад

      Already uploaded

    • @rog0079
      @rog0079 2 года назад

      @@UnfoldDataScience Can you provide the link for the same? I cannot seem to find it on your channel...

    • @232aish
      @232aish 10 месяцев назад

      @@UnfoldDataScience Hi Sir, great explanation, I cannot find the video for the code of user-based collaborative filtering, can you share the link for that? I do not think anyone can find it.

  • @DBClipss
    @DBClipss 2 года назад +1

    is "KNN item-based collaborative filtering" algorithm used to build this system?

  • @fahadnasir1605
    @fahadnasir1605 Год назад

    Hi Aman,
    Did you create a video for user based CF, if not, then please count my vote and kindly put the efforts in it :)

  • @vishalgarg7207
    @vishalgarg7207 3 года назад

    Nicely explained, can I get the Jupiter notebook for the same ? Secondly is there any code base explanation of UBCF ? Well what I used is Pearson correlation for UBCF can you shed some light or if you have any python base implementation of UBCF ?

    • @UnfoldDataScience
      @UnfoldDataScience  3 года назад

      Hi Vishal.
      drive.google.com/drive/folders/1aBH3S0YnGi8sw7C2wtUDF181ETXbfikb

  • @aszx204
    @aszx204 2 года назад

    sir, i want to ask..
    so basically we have to find what movie recommendations based on particular movie one by one?
    in this video you give example Fargo. if there are 100 movies, we have to do this 100 times?

    • @raghavverma120
      @raghavverma120 2 года назад

      yes! You can automate that by creating functions, and keep updating the matrix..

  • @sadhnarai8757
    @sadhnarai8757 4 года назад +1

    Very Good Aman

  • @DS_AIML
    @DS_AIML 4 года назад

    Crisp Explanation.

    • @UnfoldDataScience
      @UnfoldDataScience  4 года назад +1

      Thanks Anjani. Hope u r doing good!

    • @DS_AIML
      @DS_AIML 4 года назад

      @@UnfoldDataScience I am good.Thankyou.Hope you are doing good too.

  • @urspappuyt
    @urspappuyt 3 года назад +1

    Hello sir... what if there are no ratings for a product and i want to work with implicit data without ratings based on products added to cart. Can you please tell me

    • @urspappuyt
      @urspappuyt 3 года назад

      Please reply to my query

    • @UnfoldDataScience
      @UnfoldDataScience  3 года назад

      YOu need to create rating artificially.
      For example "how many times a product is viwed by user"
      "time spent on product" etc

  • @mariaanastasya2619
    @mariaanastasya2619 4 года назад +1

    So cool! Thank you sir. I want to ask about the deep item based collaborative filtering. Is it the same way to implement it in python? Thanks in advance.

    • @UnfoldDataScience
      @UnfoldDataScience  4 года назад

      Hi Maria, concept wise same, little different data preparation wise :)

    • @mariaanastasya2619
      @mariaanastasya2619 4 года назад +1

      @@UnfoldDataScience About the data sir, cause this is about deep learning.. so we need large data? is it right? or something else?

    • @UnfoldDataScience
      @UnfoldDataScience  4 года назад

      Yes more data is better for deep learning model.

    • @mariaanastasya2619
      @mariaanastasya2619 4 года назад

      @@UnfoldDataScience Hallo sir, i want to ask something about deep learning algorithm such as BiLSTM, my team decided to make a book recommendation system with bilstm. what type of data is correct to use? we have plan to use data transaction borrow book from bookcrossing. what do you think about it? Thank you in advance.

  • @EngRiadAlmadani
    @EngRiadAlmadani 4 года назад +1

    Good jop

  • @1oneohad
    @1oneohad 3 года назад

    really like your videos, very clear and fun to listen to!
    i got 3 questions.
    first, what about normalizing the values of the user ratings as you said in previous videos?
    second, how can you use the ready UII matrix afterward in an application without running all the calculations from the start?
    third, which one is better, user based CF or Item based CF?
    thank you!

    • @UnfoldDataScience
      @UnfoldDataScience  3 года назад

      1. Normalization will apply here as well
      2. Save it as python object object and use later
      3. Depends on data and use case

    • @salvadorshane1802
      @salvadorshane1802 3 года назад

      InstaBlaster...

  • @preranatiwary7690
    @preranatiwary7690 4 года назад +1

    Good information!

  • @sudipbose2513
    @sudipbose2513 3 года назад

    Sir I have made a music recommandation system in jupiter. How can I apply this model in website which can recommand songs popularity based or item based..pls help me sir

  • @tahreemzahoor5461
    @tahreemzahoor5461 3 года назад

    Can u plz explain me..why we get high correlation in those movies which have been rated by only 5 our less then 10 users...........and plz explain how to evaluate this CF-I

    • @UnfoldDataScience
      @UnfoldDataScience  3 года назад

      The reason for that may be low data points. You can take these movies in a separate analysis.

  • @ridakhan7934
    @ridakhan7934 Год назад

    If we want to apply pearson correlation on selected features so, when and how it should be done?
    if you have any video related to it please suggest me.

  • @joancarreras351
    @joancarreras351 3 года назад

    Hi, Thank u for the video! I've seen that you haven't post the User-based code and I can't find it on your drive. Could you provide it?

    • @UnfoldDataScience
      @UnfoldDataScience  3 года назад

      Does this help?
      ruclips.net/video/pGt4XMtyWm0/видео.html

    • @rog0079
      @rog0079 2 года назад

      @@UnfoldDataScience This is the theoretical part, people are asking about the code tutorial for user-based collaborative filtering...

  • @Bawaromerali
    @Bawaromerali 3 года назад

    Thanks

  • @wise1569
    @wise1569 4 года назад

    What if ratings are not given then how recommendation system built?

    • @UnfoldDataScience
      @UnfoldDataScience  4 года назад

      There are ways to use other features as rating. For example - No of views by a user can be used in place of rating.

  • @ranag9336
    @ranag9336 3 года назад

    can you show this code work in VS code,,i am getting error there.thankyou. New subscriber

  • @chodeyalekhya8204
    @chodeyalekhya8204 3 года назад

    Sir plz can u provide code for collaborative filtering and content based in the purpose of movie recommedtion system.

    • @UnfoldDataScience
      @UnfoldDataScience  3 года назад

      Hi Chodey, code for this use case is already uploaded here:
      drive.google.com/drive/folders/1XdPbyAc9iWml0fPPNX91Yq3BRwkZAG2M

  • @shivampandiya894
    @shivampandiya894 3 года назад

    Sir plz can u provide code for user based in memory based collaborative filtering.

    • @UnfoldDataScience
      @UnfoldDataScience  3 года назад

      All codes and data here:
      drive.google.com/drive/folders/1XdPbyAc9iWml0fPPNX91Yq3BRwkZAG2M

  • @warrior_1309
    @warrior_1309 4 года назад

    Thanks sir.

  • @bhavkeeratsingh4986
    @bhavkeeratsingh4986 3 года назад

    Hello sir,I want to make a job recommendation system based on user's features like location,his skills,gender etc.I want to compare these features with my dataset to show jobs with most relevant jobs.Can u pls help .I m struck

    • @UnfoldDataScience
      @UnfoldDataScience  3 года назад

      You can prepare data at user level and run collaborative filtering.

    • @bhavkeeratsingh4986
      @bhavkeeratsingh4986 3 года назад

      @@UnfoldDataScience So should I prepare a dummy user profiles dataset?

    • @bhavkeeratsingh4986
      @bhavkeeratsingh4986 3 года назад

      @@UnfoldDataScience Sir actually my problem is like a restaurant suggestion app in which a user selects his food preferences (like indian,Chinese) etc and I want to recommend shops which are according to his preferences.Its like a cold start problem I have restaurant data but my user is new

  • @phanikumar3136
    @phanikumar3136 4 года назад

    plz post a video wrt user based cf

  • @DS_AIML
    @DS_AIML 4 года назад

    Please create User Based Collaborative Filtering Model

    • @UnfoldDataScience
      @UnfoldDataScience  4 года назад +1

      User based also I had plan of creating. Will create for sure. Thanks for the suggestion.

  • @shivajiavhad1903
    @shivajiavhad1903 4 года назад

    i want to create a recommendation where i can recommend user post with similar category he likes ....

    • @shivajiavhad1903
      @shivajiavhad1903 4 года назад

      how can i ?

    • @UnfoldDataScience
      @UnfoldDataScience  4 года назад +1

      Hi Shivaji, you can create data with user item similarity and then go to running a model.

    • @shivajiavhad1903
      @shivajiavhad1903 4 года назад

      @@UnfoldDataScience didnt understand ...can u elaborate or show me example video

  • @esaalfitra1153
    @esaalfitra1153 3 года назад

    pak deadline saya besok mohon cepat di upload yang user content rekomendasi

  • @MrRobo930
    @MrRobo930 3 года назад

    Post UBCF