Pavan Kalyan Urandur's repositories
Machine-learning-without-any-libraries
This is a collection of some of the important machine learning algorithms which are implemented with out using any libraries. Libraries such as numpy and pandas are used to improve computational complexity of algorithms
Machine-Learning-Using-Scikit-learn-and-other-libraries
Machine Learning algorithms implementation using Python
Digit-Recognition-from-0-to-9-in-python
Digit Recognition(from 0 to 9) using sklearn ensemble and random forest classifier
machine_learning_examples
A collection of machine learning examples and tutorials.
Advanced-Machine-Learning-Assignments
This repo contains assignments for the specialization of Advanced Machine Learning Course in coursera
Algorithm-Visualizer
This project involves developing a tool which will visualize Data Structures and Algorithms. Important algorithms like Sorting, Graphs, Linked List, Trees etc will be implemented. I have used React Js for developing the tool
CoronaVirus-Tracker
This repository is a mini project for Tracking Corona virus using Coronavirus COVID-19 Data. A dash board has been created which shows number of reported cases, deaths and recovered cases followed by detailed description of geography wise information. I used Java, Spring Boot, Thymleaf for building the application.
covid19-tracker
This is a react application used to monitor COVID-19 Statistics. I have used Material UI to build the UI and axios to fetch data from COVID-19 api
Deep-learning-Frameworks
Some of the deep learning projects using Programming Frame works like Tensorflow, Pytorch, Keras etc
DeepLearning.ai-Summary
This repository contains my personal notes and summaries on DeepLearning.ai specialization courses. I've enjoyed every little bit of the course hope you enjoy my notes too.
DocsAPP
This app is created as a part of final year engineering project. This is a prototype of the idea of communication between doctor and patient via android app. The patient can fix appointment with doctor via App, Doctor can send message to pharmacy and diagnostic centre of all the medicines and Diagnostic tests via App. Pharmacists and Diagnosticians can even send the reply to doctor telling the status of the tasks assigned to them. Back end of the project is coded in Google firebase, a convenient nosql database.
GenderFromNames
This repo contains model Trained using LSTM(Long Short term Memory) in keras for predicting the gender of people given their names. Approximately 92% Training Accuracy,89% Validation Accuracy and 89% Testing accuracy has been achieved after training for 25 epochs on 76000 training examples.
Housing-Price-Predictions
This repo do data analysis with California Housing Prices dataset from the StatLib repository.
Intelligent-QR-Code-generator-for-baggage-content-monitoring
The project Intelligent QR Code generator for baggage content monitoring is done as a part of curriculum for the course "Product Design and Development". Project aims at developing a simple GUI which takes user details like Name,Address,Passport Number as Input and generate a QR code tag which contains area wise percentage of metallic and non-metallic components in user's baggage. It uses X-ray images generated by X-ray baggage scanner (often present in airports). Project code is written in python and uses Tkinter and open cv packages.
K-Means-Clustering-Python-Implementation
A random two dimensional data set is generated with 1000 examples. K Means clustering algorithm is performed on those examples to find the patterns in them. Results have been visualized. Note that this is only for practice
Let-s-Chat
Android Application which serves as a messaging app between two users.
LinearRegression-WeatherHistory-
Simple linear Regression to predict Temperature and Apparent temperature from humidity. Dataset was download from Kaggle
MOOC-Coursera-Advanced-Machine-Learning
Content from Coursera's ADVANCED MACHINE LEARNING Specialization (Deep Learning, Bayesian Methods, Natural Language Processing, Reinforcement Learning, Computer Vision).
Python-Implementation-of-Andrew-Ng-Machine-learning-Course
This repository contains programming exercises implemented using python for the course of Machine learning by Andrew Ng coursera. Original Programming exercises were implemented using matlab/octave. This project gives indepth understanding of Machine learning algorithms discussed by Andrew ng in original course.