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ar-cutpaste

Cut and paste your surroundings using AR

awesome-nlprojects

List of projects related to Natural Language Processing (NLP) that make a geek smile for they exist

back-end-developer-interview-questions

A list of back-end related questions you can be inspired from to interview potential candidates, test yourself or completely ignore

building-multi-tenant-applications-with-django

carnd-detect-lane-lines-and-vehicles

Use segmentation networks to recognize lane lines and vehicles. Infer position and curvature of lane lines relative to self.

carnd-vehicle-detection

Vehicle Detection Project

copilot

Lane and obstacle detection for active assistance during driving. Uses windowed sweep for lane detection. Combination of object tracking and YOLO for obstacles. Determines lane change, relative velocity and time to collision

covid-19

Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE

daily-coding-problem

Solutions to problems sent by dailycodingproblem.com

datasciencecoursera

Data Science Toolkits Project.

datasharing

The Leek group guide to data sharing

deeptl-lane-change-classification

Driving risk assessment with deep learning using a monocular camera. Related paper: https://arxiv.org/abs/1906.02859

democrance_backend

django-notifications

GitHub notifications alike app for Django

errand

event_error_reporting

django event and alert reporting.

generating-text-small-corpus

Generating style-specific text from a small corpus of 2.5k sentences using a pre-trained language model. Code in PyTorch

html-exercise-file

interactive-coding-challenges

120+ interactive Python coding interview challenges (algorithms and data structures). Includes Anki flashcards.

jobber

jobfinder

Job portal based on Django and sqlite database. it has everything job portal should have

laravel-realworld-example-app

Exemplary real world backend API built with Laravel

mongo

The Mongo Database

movie-recomender

Recommender System is a system that seeks to predict or filter preferences according to the user’s choices. Recommender systems are utilized in a variety of areas including movies, music, news, books, research articles, search queries, social tags, and products in general. Recommender systems produce a list of recommendations in any of the two ways – Collaborative filtering: Collaborative filtering approaches build a model from user’s past behavior (i.e. items purchased or searched by the user) as well as similar decisions made by other users. This model is then used to predict items (or ratings for items) that user may have an interest in. Content-based filtering: Content-based filtering approaches uses a series of discrete characteristics of an item in order to recommend additional items with similar properties. Content-based filtering methods are totally based on a description of the item and a profile of the user’s preferences. It recommends items based on user’s past preferences. Let’s develop a basic recommendation system using Python and Pandas. Let’s focus on providing a basic recommendation system by suggesting items that are most similar to a particular item, in this case, movies. It just tells what movies/items are most similar to user’s movie choice.

odoo

Odoo. Open Source Apps To Grow Your Business.

pygta5

Explorations of Using Python to play Grand Theft Auto 5.

pypaystack

A django reusable app for integrating Paystack into your application

python-deep-learning-projects

Python Deep Learning Projects, published by Packt

python-tutorial

Python tutorial series

python_data_science_and_machine_learning_bootcamp

Jupyter notebook for Udemy course: Python data science and machine learning bootcamp