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algorithms

Minimal examples of data structures and algorithms in Python

api-integrations-python

This repository includes different types of API integrations with Python.

atm-project

file processing project

binary-search-tree-progams

calculator-app-with-python

ganesh kavhar python projects..

call-break-the-card-game-in-python

The Call Break (Lite) - A Card Game Project in Python with Explanation

chatterbot

ChatterBot is a machine learning, conversational dialog engine for creating chat bots

cloudlabs-azure

Azure Labs on CloudLabs.AI

credit_card_fraud_detection

This is a classification problem to detect or classify the fraud with label 0 or 1. Class with label 1 means fraud is detected otherwise 0. The biggest challenge is to handle the imbalanced data set.

dive-into-machine-learning

Dive into Machine Learning with Python Jupyter notebook and scikit-learn!

face_recognition_based_attendance_system

A python GUI integrated attendance system using face recognition to take attendance.

faker

Faker is a Python package that generates fake data for you.

github-readme-stats

:zap: Dynamically generated stats for your github readmes

guessing_game_using_pygame

This a picture memorization game that is developed using pygame.

hacktoberfest2020

Make your first PR! ~ A beginner-friendly repository. Add your profile, a blog, or 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 to add the file under the correct directory. Happy hacking!

hearthealthprediction

The major reason for the death in worldwide is the heart disease in high and low developed countries. The data scientist uses distinctive machine learning techniques for modeling health diseases by using authentic dataset efficiently and accurately. The medical analysts are needy for the models or systems to predict the disease in patients before the strike. High cholesterol, unhealthy diet, harmful use of alcohol, high sugar levels, high blood pressure, and smoking are the main symptoms of chances of the heart attack in humans. Data Science is an advanced and enhanced method for the analysis and encapsulation of useful information. The attributes and variable in the dataset discover an unknown and future state of the model using prediction in machine learning. Chest pain, blood pressure, cholesterol, blood sugar, family history of heart disease, obesity, and physical inactivity are the chances that influence the possibility of heart diseases. This project emphasizes to evaluate different algorithms for the diagnosis of heart disease with better accuracies by using the patient’s data set because predictions and descriptions are fundamental objectives of machine learning. Each procedure has unique perspective for the modeling objectives. Algorithms have been implemented for the prediction of heart disease with our Heart patient data set

image_detector-using-python-libraries

PROJECT(Image_detector)_using_python_Libraries

miniproject

morse-code-translator

A morse code translator which can convert plain text into encrypted form as morse code and also it can convert morse code back into plain text.

movie-recommendation-system-using-python-and-pandas

This is a python project where using Pandas library we will find correlation and give the best recommendation for movies.

pacxon

python-fire

Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.

python-gui

Gui Projects in Python 3 and PyQt5

python-media-player

Simple Music Player Written in Python And Tkinter

python-projects

Amazing Python Projects.

python-telegram-bot

We have made you a wrapper you can't refuse

quixel

quixel is an open source project for text content analysis semantically.

rich

Rich is a Python library for rich text and beautiful formatting in the terminal.

self-driving-cars-updated-

signature-recognition

Signature recognition is a behavioural biometric. It can be operated in two different ways: Static: In this mode, users write their signature on paper, digitize it through an optical scanner or a camera, and the biometric system recognizes the signature analyzing its shape. This group is also known as “off-line”. Dynamic: In this mode, users write their signature in a digitizing tablet, which acquires the signature in real time. Another possibility is the acquisition by means of stylus-operated PDAs. Some systems also operate on smart-phones or tablets with a capacitive screen, where users can sign using a finger or an appropriate pen. Dynamic recognition is also known as “on-line”. Dynamic information usually consists of the following information: