@DevJoshi0Hello! These are my final hack sessions for my movie sentiment analysis bot, I’m still away from my computer until the first week of September but I don’t want the 8 hours of progress on the bot and website part to be wasted. It’s not a finished product and the only progress is my backend and a few changes to the bot itself. Apologies if this isn’t allowed to be on scrapbook I just didn’t want to leave 8 hours to not be reviewed github.com/devjoshi0/Movie-Sentiment-Analysis
The bot itself is still usable it’s just the website that isn’t displayed properly. I am sure to make progress once I come back but that’ll be after hack club since it ends August
@000xs0MovieBuddy is an intuitive movie discovery platform featuring curated categories like Popular, Top Rated, and Upcoming movies. With a sleek and responsive design, users can easily browse and explore the latest films, view detailed movie information, and enjoy an engaging cinematic experience on any device.
Repo : github.com/000xs/moviebuddy
Live : moviebuddy-8h099noi7-sithumsathsaras-projects.vercel.app
@RishiShah0I conducted text classification with BERT on the imdb datasets. I did sentiment analysis on the imdb dataset, which has movie reviews labelled as positive or negative. I loaded a pre-trained BERT model and then fine tuned it on the dataset.
github.com/Shahrishi4324/TextClassification
@RishiShah0I made a project that involves building a sentiment analysis model to classify movie reviews as positive or negative. I used SpaCy for text preprocessing and Scikit-learn for model training and evaluation.
github.com/Shahrishi4324/MovieReview
@IshikaKumar0ever since i watched "Who Framed Roger Rabbit?" for the first time this summer (A+ movie, 10/10, highly recommend) i really wanted to draw Jessica Rabbit cause I love her character design and she's an icon ✨
so i did that :)
yippee !!
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repository: github.com/Liana24601/jessica-rabbit-drawing/tree/main
(as always, reviewers, you guys are amazing and thank you for dedicating your time for this 💗)
@DevJoshi0Hello! I made a sentiment analysis bot which takes the name of a movie as input in the terminal and uses nltk and a dataset in order to give a sentiment rating. I plan to implement this into a website using React + Vite and Flask. Here is the code, ignore the backend and frontend folders since I was making progress on the website for a while but I wasn't sure if I'd be able to finish it before the end of August since I'm visiting family till september.
github.com/devjoshi0/Movie-Sentiment-Analysis
if you'd like to run the code, run the (scraping.py) file on the terminal. After downloading the repo. Ill add more instructions in the README file as soon as possible
@Silvia0analysed movie data and displayed it #arcade
@Stefan0I created a Movie Recommendation AI in AstroJS, powered by OpenAI GPT-4o-mini, and TMDb for poster art.
Repo: github.com/Naainz/Movie-AI
Demo: movie-ai-one.vercel.app
Please note that if you try to use the demo, it will not give perfect recommendations, as it is using cached data, previously provided from AI. I can't afford to support many users through my $3 OpenAI balance, so if you want to reproduce the AI, and try it for yourself, visit my repo, and follow steps in the readme.
@ShreyasJain0Post 16
🎥 Moviefy 🎵
Moviefy is a web application that allows users to search for movies and automagically generate a Spotify playlist with the movie's soundtrack. The application leverages the OMDb and TMDb APIs for movie data and the Spotify API for creating playlists.
Key Features
• Integrated Client/Server: Seamless communication between the React/Next.js frontend and Node.js/Express backend.
• Working Endpoints: Fully functional endpoints for searching movies and handling Spotify authentication.
• Movie Searching: Search for movies using the OMDb API & JSON queries.
• Spotify OAuth: Authenticate with Spotify to create and manage playlists.
Work In Progress Features
• Fetching Soundtrack: Retrieve the soundtrack of a movie (currently a work in progress).
• Creating Playlist: Automatically create a Spotify playlist with the retrieved soundtrack (currently a work in progress).
Check it out @ github.com/shrysjain/moviefy
