himalaypatel Goto Github PK

angular.js

AngularJS - HTML enhanced for web apps!

autorccar

OpenCV Python Neural Network Autonomous RC Car

awesome-courses

:books: List of awesome university courses for learning Computer Science!

awesome-public-datasets

A topic-centric list of HQ open datasets. PR ☛☛☛

babylon.js

Babylon.js: a complete JavaScript framework for building 3D games with HTML 5 and WebGL

blynk-library

Blynk library for embedded hardware. Works with Arduino, ESP8266, Raspberry Pi, Intel Edison/Galileo, LinkIt ONE, Particle Core/Photon, Energia, ARM mbed, etc.

bootstrap

The most popular HTML, CSS, and JavaScript framework for developing responsive, mobile first projects on the web.

breast-cancer-classification

Used Support Vector Machine to classify a given image from breast cancer wisconsin dataset (sklearn) into malignant or benign cancer.

chart.js

Simple HTML5 Charts using the <canvas> tag

cis521

Intro to Artificial Intelligence (Don't steal my code bro!)

credit-card-fraud-detection

Implemented Decision Tree, Random Forest and Deep Neural Network (5 layers) on a real anonymized dataset. Used undersampling and oversampling (SMOTE) with Deep Neural Network to balance the highly imbalanced dataset (very less fraudulent transactions as compared to non-fraudulent ones). Achieved 99.6% test accuracy using SMOTE with NN along with 0 Type-II errors (false negatives).

cs-180

UCLA CS 180

customer-subscription-direction

Used Logistic Regression Classifier to decide whether a customer should be directed to subscription by analyzing his app behavior. Also implemented k-fold Cross Validation to prevent overfitting.

django

The Web framework for perfectionists with deadlines.

dlib

A toolkit for making real world machine learning and data analysis applications in C++

ember.js

Ember.js - A JavaScript framework for creating ambitious web applications

face_detect_n_track

Fast and robust face detection and tracking

face_recognition

The world's simplest facial recognition api for Python and the command line

fashion-class-classification

Implemented Convolutional Neural Network to classify images from MNIST Fashion Class dataset into 10 different classes.

flask

A microframework based on Werkzeug, Jinja2 and good intentions

game-of-life

Demo application for the 'Jenkins: The Definitive Guide' book

hello-world

My first repository

home-security-system

Built system to recognize faces and give access to home, based on access profile (family, friend, intruder) in database. Possesses multi-level security. (PIR motion sensor inside for motion detection and webcam outside home for surveillance and face recognition) Owner/s can access system remotely and can also see live video surveillance on mobile phones/PC at any time. (Check out test_videos.txt for links to YouTube videos to see the project in action!)

jgraphx

jquery

jQuery JavaScript Library

linux

Linux kernel source tree

loan-likelihood-prediction

Implemented following algorithms to solve the problem- Logistic Regression (with Lasso penalty), SVM (with linear and RBF kernels) and Random Forest (with 100 decision trees and Entropy & Gini impurity). Also used Grid Search to tune hyperparameters of Random Forest classifier. Achieved initial test accuracy of 56.2% with Logistic Regression and increased to 63.5% with Random Forest + Gini impurity.

meteor

Meteor, the JavaScript App Platform

milq

Useful code of Manuel Ignacio López Quintero

minimizing-churn-rate

Applied Logistic Regression to a dataset of customers’ financial habits artificially created from real life case studies. Achieved test accuracy of 62.9%. Used Undersampling to balance the dataset, k-fold cross validation to improve accuracy and Recursive Feature Elimination to reduce chances of overfitting.