Atul Kumar's repositories
MovieDekho
Android App Assignment
competitive_programming_course
A completely free course on data structures , algorithms and competitive programming.
Computer-Networks-Notes
Notes based on the book "Computer Networking, a top down approach"
chapel
a Productive Parallel Programming Language
EasyUpiPayment-Android
📱Android Library to implement UPI Payment integration easily in Android App 💳💸
maang-1
🏆 Winning Project of (Smart India Hackathon 2019) for the problem statement KK4.
susi_android
SUSI.AI Android App https://play.google.com/apps/testing/ai.susi
codeheat.org
Codeheat Coding Contest Website https://codeheat.org
DS-Algo
Make your first PR! ~ A beginner friendly repository made specifically for open source beginners. Add any program under any language (it can be anything from a hello-world program to a complex data structure algorithm) or update the existing one. Just make sure you add the program under the correct language directory. Happy codingImplementation of specific algorithms and data structure used and problem based on that algorithms(C++/JAVA/PYTHON)
open-event-attendee-android
Open Event Attendee Android General App https://github.com/fossasia/open-event-android/blob/apk/open-event-dev-app-playStore-debug.apk
android-1
📱 Nextcloud Android app
Travel-Mate
A complete travel guide!
kiwix-android
Kiwix for Android
neurolab-android
NeuroLab Android https://github.com/fossasia/neurolab-android/raw/apk/neurolab-dev-debug.apk
C-Plus-Plus
All Algorithms implemented in C++
open-event-organizer-android
Open Event Mobile App for Organizers and Entry Managers https://play.google.com/store/apps/details?id=com.eventyay.organizer
pslab-android
PSLab Android App https://play.google.com/store/apps/details?id=io.pslab
android
Amahi Android App
mifos-mobile
Repository for the Mifos Mobile Banking App for clients
android_guides
Extensive Open-Source Guides for Android Developers
Chhatrawas
An Android application created in HackNITP 2019 event for hostel management. It got the first Position in the event! It was designed and written from scratch in less than 30 hours with my three other teammates. This app does what it was built for so don't judge us for not using Industry levels design principal like MVVM or MVP 😜
TaxiFare
An app to predict the fare of NYC taxis and compare them with live fares of Uber and Lyft taxi providers. It uses Neural Network trained on 50 million taxi trips to predict the fare. It uses Uber API and Lyft API to provide live fares and directly book a ride through Uber and Lyft apps and uses Mapbox API to plot a map between source and destination. TaxiFare utilizes Django framework to connect the Python training code and Android.