himankckalal Goto Github PK
Name: HIMANK KALAL
Type: User
Company: Coep
Name: HIMANK KALAL
Type: User
Company: Coep
This dataset contains 207,572 books from the Amazon.com, Inc. marketplace.
Classification of books based on titles without prior knowledge of context or author
Recommendation System
A simple Book Recommendation System with basic data mining techniques
Tag-Based Book Recognition System
Final project for the Master in Data Science at Kschool
The book recommendation system is based on the Item based collaborative filtering technique. The script is written using pyspark on top of Spark's built in cluster manager. It is used to recommend similar books to each other based on the ratings and the strength of the ratings.
content-based book recommendation system using tf-idf/countvectorizer; rating prediction using deep learning
A simple book recommendation system using Collaborative filtering and demographic information of user
A recommender system built for book lovers.
A book recommendation system using Collaborative Filtering
A Tensorflow implementation of Collaborative Metric Learning (CML)
This repository consists of data helpful for ACM ICPC programming contest, in general competitive programming.
Important Books for Computer Science Students for Algorithms
The Cricket World Cup Tournament Scheduling with Constraints.
A collection of 300+ Jupyter Python notebook examples for using Google Earth Engine with interactive mapping
Book Crossing Recommendation System
Using Google Ads API to create and upload user list.
Thanks to lirenTu@scale
A content-based recommender system for books using the Project Gutenberg text corpus
Config files for my GitHub profile.
A Hybrid Recommendation system which uses Content embeddings and augments them with collaborative features. Weighted Combination of embeddings enables solving cold start with fast training and serving
This is a book recommendation engine built using a hybrid model of Collaborative filtering, Content Based Filtering and Popularity Matrix.
This project contains Latent Factor based collaborative Filtering Recommendation Engine with optimized code which handles complexity problems with sparse matrices too.
In this repository, I upload my Complete Machine Learning code which I have learned from different courses(Coursera, udemy, edx, udacity), different websites blogs, different tutorials from YouTube, books, and research papers. I have covered both Supervised and Unsupervised Machine Learning Algorithms with Practical Implementation.
machine learning and deep learning tutorials, articles and other resources
Python code for common Machine Learning Algorithms
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.