Project 18. Movie Recommendation System using Machine Learning with Python
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- เผยแพร่เมื่อ 5 ก.ย. 2024
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. In this video, I explained how to build a Movie Recommendation system using Machine Learning with Python. This is one of the most important Machine Learning Projects.
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Brother your project is amazing but you have created your own machine lerning model for movie prediction.. I thought you are going to use what already existed but overall was a good learning video.. Thank you😊
Thank you very much for your support in jamia hamdard university I had done this for 6 semester project😁
Gautam Tripathi will fire u 😂😂
Thanks you so much Sir. Because of you now I start to understand machine learning.
first machine learning project .....helped a lot.......... thank you
Hey ! just wanted to tell you that you make amazing projects ... and please make project on COVID-19 Data Analysis
Thanks you @Siddhardhan, This was very informative project that you shared with us. It will be helpful for beginners to build more projects like this
Another video today , exiting
You are preety fired up these days
Thanks 😇
Salutes to you bro... very neatly explained and I have also done the coding... Thanks a lot... lot of new information covered in this... thank you....
Hello please help me
Thank you sir for this wonderful project and explaination.
broh, thank you so much! Cheers, very easy to understand and at the same time not slow! Wonderful project s2
Thank you sir for the amazing video. Wonderfully explained👍
thank you, thank you, all our best to u and yours.
SECRET MESSAGE project-
In this project you will create a
program that will take the
names of the files and decrypts
the secret message in the file.
Sir pls make vedio on above topic 🙏🙏
excellent explanation thank you very much
bro please take courses about data visualization and power bi bro! awesome projects!
Brother this is a great tutorial, thanks a lot for sharing your knowledge.
sach me kamal ka video hai THANK U SIR love u...
I created this on a gui window it worked well and looked beautiful thanks you are doing a great job helping ppl like me❤️
You're most welcome 😇
Can you share the code for gui window please?
@@sabinchaudhary3515 +1
@@sabinchaudhary3515 you can use Streamlit to do that, pretty easy and understandable.
@@nikhiljagtap1669 Can you share the code?
This is a marvelous job. Keep it up.
thank you so much for this video, it has been extremely helpful and I'm very grateful. My doubt is; when we use TfidfVectorizer() library we are using an instance and then accessing a function inside the library. But, when we use the difflib library we are directly using it and accessing the get_close_matches function inside it without assigning an instance. Why are we doing this and what is the difference between the two that is causing us to differentiate between the two?
Too much excited for this project
Happy learning 🙌😇
Ohh I really like the way you explain everything! Thanks sir
Can I know what is popularity column in the dataset and how it was calculated?
Excellent project and explication, it was amazing!!!!!
This video is just awesome💯👌,Thank you❤
Thank you for your clear explanation and great effort sir. And what is evaluation techniques to evaluate these content based recommendation systems sir, Could you please answer it will be more helpful sir
The best!
Great tutorial bhaiya! Thanks for this!
Thanks bro😊.
very informative.. thank u for making such videos
Brilliant tutorial, thank you.
At x1.25, a full stop in his sentences doesn't apply. But still a great job bro..!!
Perfect explanation so as a perfect project thank you Sir
You are welcome
Thank you so much! Explained so clearly!!!!
It's awesome thanks a lot sir you have explained it in a very beautiful manner again thanks a lot to you for making such a great video❤️❤️
I just want to know thar how can I make the interviewer understalnd this project pls advice me.......
Amazing tutorial my friend! Kudos!
amazing video sir...thank u👍
Hello sir ek error aa raha ha mera...can you plz help?
find_close_match = difflib.get_close_matches(movie_name, list_of_all_titles)
iss line pe bol raha ha ki......" can't have more matches than the number of elements in the shorter sequence "
Ye kaise resolve karu
I'm having the same error (I only speak english by the way sir!)
Awesome video, thank you so much!
This is so amazing, thank you
loved the video, thanks a lot!
Glad you enjoyed it!
Thank You very Much Sir
Thanks for the great video!
amazing explanation
great project ,thak you sir
hello sir, the video is great
But I also want to know the degree of accuracy of your prediction? How will you do that?
Like you used cosine similarity and claimed some prediction but somebody else will use another algorithm and claims that his algorithm is giving more accurate prediction than yours.
So, how to check what is the accuracy of your prediction?
I would think companies answer that question with user metrics and feedback
Thanks a lot !
Great tutorial! Thank you very much
But I have a problem. The algo doesn't work with some movies. For instance, when I search "x men" or "indiana jones", I don't get a good match
as we are not using any model here, is there any possible way to save model or there is something like pre-traineed model in recommender system????
❤❤❤❤❤❤❤❤❤
what was the point of using difflib when you had cosine similarity anyways?
Sir can u tell which algo is used in this project
Thankyou veryy much for this video!! your explanation is amazing.
Thank you bro ❤❤❤❤
thank you so much bro
the content of the video is really great and understandable easily...
but i get an error here sir.
here the statement for getting the input from the user is running continuously with the in[*] sign. what should i do know sir?
which recommendation technique you used ? whehter it is content-based ??
finished watching
which model is used in this?
sir, how can i evaluate the accuracy of the model?
Sir make a video on that projects which we can add to our resume and please make us understand how we can deploy this movie recommendation system step by step.
Write 'get_feature_names_out'
You are the best!
😇
sir at difflib that type conversion error is coming sir i can't able to fix it help me from this with any solution
Where is the Dataset from?
After a long time with a firing video. Welcome back.
thanks
You are great man!
😇😇
Hello Siddhardhan. How do we build a pipeline for this project? It would be great if you could help me. Thanks
Sir i used different data set and shows that ParserError what can I do?
my similarity value is stuck at 1 no matter how i change t. Help!!
great video!
والله انت راجل فهمان
for some input data it is showing index out of bounds
Please tell me uniqueness of this project ??
My teacher is asking me ....please tell me uniqueness of this project
Sir what are the problems can be solved by recommender system project?
My dataset is not showing in my colab after 1 sec. How can I increase the time
Sir can we have report for this project
combined_features has 1 column or 24?i didnt understand.
What If the user gave the input that doesn't contain in the dataset,will it work then ?
Thank you very much for your help, your channel is great!
Thanks Man !
Thanks bro
brilliant work fam, loved this one
sir plz tell how to check accuracy too
ohhh is god but cant run always my code some error is found why?
helpful
Sir, what is the machine learning algorithm is used in this project?
So have u got the answer bro? What algo is used?
@@jiohome3950 cosine similarity is not an algorithm. It’s a mathematical framework used in many machine learning task
@@michael3226 so what's the algorithm bro? Can you plz tell ...i want to know
@@jethalal9473 one can say Cosine Similarity is the main tool used as it measures the similarity between two non-zero vectors of an inner product space, and it calculates the cosine of the angle between them, Giving recommendations as it’s use case here.
Conventional ML algorithms include: SVM, KNN, Linear Reg, Logistic Reg and co.
@@michael3226 have you ever done ml project in react ?
Can you please tell me which machine learning algorithm is used in this project?
K vecinos más cercanos
Thanks for the video! can you please explain this line,
index_of_the_movie = movies_data[movies_data.title == close_match]['index'].value[0]. I know it is used to get the index of the movie. programmatically can u explain how it is accessing the value.
what type of recommendation system is it content or collab
how we can solve memory error if we have a dataset of around 50,000 rows while doing cosine similarities?
same problem happened to me, while i have tried with another dataset. I checked with the stack over flow , but still i hadn't get the solution for the problem
Sir can we convert it in web pages by using flask and html ?
which algorithm is used in this project
Nice
Thanks
Best!!
😇
How to build this system recommendations in Java
Nice 👍🏻 but Make video on new problems its already available on internet, its a old project
Great video! Let's say if i want to input multiple inputs instead of 1 input, how can this be done?
Can Overview help to improve accuracy?
Can anyone help me? I want the above project to run in a website. 😔
Where is the dataset available sir ?
can you share the Kaggle link of that dataset here?