Music Recommender System Using Python
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- čas přidán 30. 06. 2024
- Creating a music recommender system using CZcams video descriptions involves using Natural Language Processing (NLP) techniques to analyze the text descriptions and recommend music based on the content. Here's a high-level overview of how you could approach building such a system using Python:
1. *Data Collection:*
- Dataset Link: www.kaggle.com/datasets/notsh...
2. *Text Preprocessing:*
- Clean and preprocess the text by removing special characters, punctuation, and converting all letters to lowercase.
- Tokenize the descriptions into individual words or phrases.
- Remove stopwords (common words like "and," "the," "is," etc.) that don't provide much context.
3. *Feature Extraction:*
- Convert the tokenized descriptions into numerical representations that can be used by machine learning models. You can use techniques like TF-IDF (Term Frequency-Inverse Document Frequency) or word embeddings (Word2Vec, GloVe) for this purpose.
4. *Building a Recommender Model:*
- Choose a recommendation algorithm. Collaborative Filtering and Content-Based Filtering are two common approaches.
*Content-Based Filtering:*
- In your case, content-based filtering might be more suitable since you're focusing on analyzing the video descriptions. This approach recommends items similar to those the user has shown interest in.
- Calculate similarity scores between videos based on their preprocessed descriptions and feature representations.
- Recommend videos that have similar descriptions to the ones the user has liked or interacted with in the past.
5. *User Interaction and Recommendations:*
- Allow users to input their preferences, e.g., by providing a sample video URL or keywords related to their interests.
- Use the selected video's description for recommendation.
- Rank the videos based on similarity scores and present the top recommendations to the user.
💻 Source Code: github.com/Chando0185/Music_R...
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Also on what basis are these vectors created and what are the X and Y axis represent that u explained in ur explanation for tokenization
Would be gr8 help if you could clear my doubts
please give me the complete code of music recommendation system because the link you share have not complete code kindly share complete code?
couldnt deploy app , streamlit is giving error for df.pkl not found .. kindly help in solving this
What to do for memory error at cosine_similarity(matrix) could you pls tell me how to correct the error
can we use lemmatization instead of stemming ?
bro, please don't use fake accent. Your natural accent is very good.
Ok bro, Thanks for suggestion
Can we add the feature of playing recommended song for user?
What algorithm did u use bro?
🔥🔥
We are getting an error in token pz can you say
sir, how can i evaluate the accuracy of the model?
I cant run using streamlit could you help me with that
what should i do :
FileNotFoundError: [Errno 2] No such file or directory: 'df.pkl'
my recommendation function is not working
def recommender(song_name):
idx = df[df['song']==song_name].index[0]
distance = sorted(list(enumerate(similer[idx])), reverse=True, key=lambda x: x[1])
song = []
for s_id in distance[1:21]:
song.append(df.iloc[s_id[0]].song)
return song
recommender("Learning To Hunt")
ans:
["She Ain't Your Ordinary Girl"]
only showing one
tokenization is not working,it shows me lookuperror
how you open these all files on vscode please explain
Also Sir how can we test the accuracy if this model??
Did you get the accuracy?
If yes can you tell me
when i call the token its did not work its give some error
Yes sir pls reply
Final Year Project Me Bhi Use Kar Sakte Hoo, Muje Acca Lagega koi Mujse Sike Python, Deep Learning Then Khut us project banake College me submit kare🌻
Actually Muje Sikane ka bohot adat he sach bolo tho Accha hi lagta he..
Sath me rehena 🤗🌼🌻
I am using it for final year project. Could you please share project report of this project with me?
What method use in this project sir? Thank you
Content based
Bro send project report
Problem Solved Just rename Df and similarity files as df.pkl and similarity.pkl and restart and run
i getting error at creating the function can you help
Did u find it…?
df.pickle file and similarity.pkl file is not created why?
You must run the .ipynb file completely to generate the df.pickle file
can you tell me the objective of this project
Bro i am gonna use this project as a Final Year Project But getting error plz help :
No such file or directory: 'df.pkl'
same probblem
@@user-lf8qe5wt5b My problem Solved bro Just rename Df file with df.pkl and similarity.pkl put .pkl to both file and project will run.
Problem Solved Just Put or rename .pkl to Df and similarity files as df.pkl and similarity.pkl
So we can only search from the sample of 5000 songs?
More data better the model
@@GuruHomelander how can I add data , if i add directly it will be different heads like text albums descs etc.
Please Share df.pkl, similarity.pkl file or You can send Folder.
I reached till studio but now I am not understanding what we have to do in studio, please help
Install python
streamlit shown blank
Why?
Sir can you please provide the Df.pkl files
Train it pls it will automatically generate
I'm stuck here, could you give us pointers please? @@knowledgedoctor3849
Got it Sir
@@knowledgedoctor3849
import pickle
pickle.dump(similarity,open('similarity.pkl','wb'))
pickle.dump(df,open('df.pkl','wb'))
@@allouchizakaria where i insert this help please
please provide -df.pkl file
import pickle
pickle.dump(similarity,open('similarity.pkl','wb'))
pickle.dump(df,open('df.pkl','wb'))
@@allouchizakariaI have to make a new file with this code only and name it as df.pkl
/r why shouldn't removed
And seminar ppt
No
please provide me pkl files
hello did you got project running then please help
did you get these ?
Please run it and you will get
run what sir the project does not run without the pkl files@@knowledgedoctor3849
Please don’t talk like this , it’s painful to hear . Indian accents are better than whatever this is .
Aah Ok, Madhumita🌻
MemoryError: Unable to allocate 23.6 GiB for an array with shape (3161436880,) and data type float64 How did u not get this error?
Take sample of the data, Seems Data Quite Big & It's Unable to allocated by YOUR memory or Use Google Colab Pro.
@@knowledgedoctor3849 is there a way i can use all songs and just store the results of distance Matrix to access it immediately everytime i need to find similarities?