Kevil Khadka's Projects
A Survey on ML Techniques for Airbnb Price Prediction
AWS is a powerful tool for learning and implementing machine learning algorithms.
Animated World Map using snap.svg.js
Insightful and beautiful visualisations to understand a dataset
A complete computer science study plan to become a software engineer.
Coursera Capstone Project
Quiz & Assignment of Coursera
Covid-19
Fundamental of Programming I
Fundamental of Programming II
Public facing notes page
Data Science Repo and blog for John Hopkins Coursera Courses. Please let me know if you have any questions.
kNN classification of hand-written digits (R)
GeoSpatial Data Handling
:zap: Dynamically generated stats for your github readmes
This repo consists of all courses of IBM - Data Science Professional Certificate, providing with techniques covering a wide array of data science topics including open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning. You will practice hands-on in the IBM Cloud using real data science tools and real-world data sets.
Official Kaggle API
Mini Projects in R using k-Nearest Neighbours
k-nearest neighbors algorithm projects
KNN Map Smoothing in R
"Classical" Machine Learning Algorithms using R
A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.
Localize and identify multiple objects in a single image.
Implement the anomaly detection algorithm which is widely used in fraud detection (e.g. ‘has this credit card been stolen?’) and apply it to detect failing servers on a network. And use collaborative filtering to build a recommender system for movies, which are used by companies like Amazon, Netflix, and Apple to recommend products to their users. Recommender systems look at patterns of activities between different users and different products to produce these recommendations.
This repo leads us to implement the K-means clustering algorithm and apply it to compress an image. And use principal component analysis to find a low-dimensional representation of face images.
Machine Learning Using MATLAB
Machine Learning: Logistics Regression Using MATLAB
Neural networks is a model inspired by how the brain works. It is widely used today in many applications: when your phone interprets and understand your voice commands, it is likely that a neural network is helping to understand your speech; when you cash a check, the machines that automatically read the digits also use neural networks.