Projects / Computer Science / Computer Science project 9

Movie and Book Recommendation Engine

Machine LearningMedium

Approx. component budget: Rs. 0 - 1,000

Objective

Build content-based, collaborative and hybrid recommenders and compare them fairly.

A recommender that suggests items based on ratings and descriptions, with a simple web interface and an explanation such as 'because you liked X'.

Similarity measures, matrix factorisation, cold start, evaluation of ranked lists, and popularity bias.

Python, pandas, scikit-learn, Surprise or implicit, MovieLens dataset, Flask or Streamlit.

Built and tested Movie and Book Recommendation Engine; objective: build content-based, collaborative and hybrid recommenders and compare them fairly.
Measured and analysed rMSE for rating prediction and precision@10 and recall@10; wrote the report and presented the results in a viva. Add your own numbers: [x].

Replace [x] with your own measured results. Write only what you really did.

The short guide for this project is prepared when you ask for it. Message us on WhatsApp and we will prepare it and tell you when it is ready.

Payment details are shared in the chat. We send the PDF on WhatsApp after your payment is confirmed.

Train and compare several classifiers and explain each prediction in simple language, so a student knows what...

Build a baseline with TF-IDF and then a transformer model, and measure how much the better model improves resu...

Train a convolutional neural network with transfer learning on a public leaf dataset and test how well it work...