Shubham Kumar's repositories
assignment-2017-2
Second assignment for the 2017 Algorithms and Data Structures course
nerd-fonts
Iconic font aggregator, collection, & patcher. 3,600+ icons, 40+ patched fonts: Hack, Source Code Pro, more. Glyph collections: Font Awesome, Material Design Icons, Octicons, & more
Partitioning-Souvenirs
You and two of your friends have just returned back home after visiting various countries. Now you would like to evenly split all the souvenirs that all three of you bought.
Python_FunctionsFilesDictionaries_finalcourseProject
Final Project of the course Python Functions, Files, and Dictionaries. This course is part of the Python 3 Programming Specialization offer by University of Michigan in Coursera. You can find more information at https://www.coursera.org/learn/python-functions-files-dictionaries/
the-unix-workbench
:house_with_garden: A Book for Anyone to Get Started with Unix
Unix_Project
Unix Final Project
Android-App-Development
This repository contains all the source code examples and the FAQ for our Android App Development Specialization for Coursera
android-mvvm-architecture
This repository contains a detailed sample app that implements MVVM architecture using Dagger2, Room, RxJava2, FastAndroidNetworking and PlaceholderView
binary-calculator
HackerRank JavaScript Challenge
CollageImageView
Sipmle library for building images collage
Datasets-1
Machine learning datasets used in tutorials on MachineLearningMastery.com
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.
Python--Candidate-Elimination-Algorithm
Problem : For a given set of training data examples stored in a .CSV file, implement and demonstrate the Candidate-Elimination algorithm to output a description of the set of all hypotheses consistent with the training examples.
Python-Decision-Tree-Using-ID3
Problem : Write a program to demonstrate the working of the decision tree based ID3 algorithm. Use an appropriate data set for building the decision tree and apply this knowledge to classify a new sample.
Python-Implementation-of-Find-S
Implement and demonstrate the FIND-S algorithm for finding the most specific hypothesis based on a given set of training data samples. Read the training data from a .CSV file