taher-software/Try-Gitflow

Stars
1
Language
Created about 3 years ago
Updated about 3 years ago

taher-software/Try-Gitflow

taher-software

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Practice Gitflow with an empty repo.

JS_Cap

In this project, we will create a Meals application with javascript and API.

car-rent-front-end

Car service Webapp where admin can add cars and delete cars. User can navigate smoothly across the differents pages, where he can explore all cars options and details, and make a reservation for a selected item and with his specific details.

Vaccine-Covid-Worldwide-tracker

A mobile web application to track vaccination rate in each country around the world.

Natural-Language-Processing-with-Disaster-Tweets

In this Kaggle competition, we’re challenged to build a machine learning model that predicts which Tweets are about real disasters and which one’s aren’t.

Jupyter Notebook

SetUpProjectWithWebpack

Hello-Rails-

Perform-automatic-image-indexing

Classical approach vs cnn approach to detect the dog' breed from his image.

Jupyter Notebook

My-Money

My-Money is amobile web application where everyone can manage his budget

Taher-web-dev

to-do-list-review

This repo, allow my coding partners to review my to do task application.

car-rent-rails

-Anticipate-aircraft-flight-delays

Simple site to predict flight delay: https://prediction-retard-avions.herokuapp.com/

Jupyter Notebook

Develop-a-proof-of-concept

New approach , state of the art in order to ameliorate the results obtained in the project titled Perform automatic image indexing.

Jupyter Notebook

testing-practice

Few practicals test using Jest library.

hello-react-front-end

Blog-app

Bookstore

Bookstore is a website use API to allow users , Display a list of books, add new book and remove selected book.

COVID19-Global-Forecasting-

Kaggle competition intend to forecast the daily spread of COVID-19 accross many regions in the word over the course between March 25 and April 22 : top 37% (196/544)

Jupyter Notebook

To-Do-List

"To-do list" is a tool that helps to organize your day. It simply lists the things that you need to do and allows you to mark them as complete. I will build a simple website that allows for doing that, and I will do it using ES6 and Webpack!

hello-rails-back-end

-Automatically-categorize-questions

Develop an API to suggest tags for a question that would be asked to Stack Overflow site.

Jupyter Notebook

Rails-with-react

Catalog-of-my-things

Catalog of my things application , is a tool which can help you to keep a record of different types of things you won: books, music albums, movies, and games..

Recipe-app

The Recipe app keeps track of all your recipes, ingredients, and inventory.

-Develop-a-movie-recommendation-engine

Movie recommandation engine who could recommend 5 similars movies to the user , based on his first choice.

Jupyter Notebook

segment-customer-behavior

This project aim to give a python application , which can allow to classify a customer to his best category , based on his previous purchases.

Jupyter Notebook

Bengali.AI-Handwritten-Grapheme-Classification

Kaggle competition which intend to accelerate Bengali handwritten optical character recognition: Public accuracy=0.951 Private accuracy=0.889

Jupyter Notebook

Leaderboard

This leaderboard website displays scores submitted by different players. It also allows you to submit your score. All data is preserved thanks to the external Leaderboard API service.

Web-dev-course-app

For this project, I've created simple responsive site for a CMS course conference. Thus, I've created home and about page with html and css. I've created menu and speakers section using javascript. I think that this work can be very useful either for someone who want to hold a confernce of web site course, or for a web developement practioner.

Optiver-Realized-Volatility-Prediction

In financial markets, volatility captures the amount of fluctuation in prices. For trading firms like Optiver, accurately predicting volatility is essential for the trading of options, whose price is directly related to the volatility of the underlying product.In this Kaggle competition,we had built models that predict short-term volatility for hundreds of stocks across different sectors. Our models will be evaluated against real market data collected in the three-month evaluation period after training.

Jupyter Notebook

Analyze-nutritional-data

My first Data science project: Exploration data analysis

Jupyter Notebook

Tunisa-Covid-Live-App

In this project, we have built a mobile web application to track covid situation in Tunisia. It provides the latest update of the main indicators. Besides, it allows to breakdown each indicators and display chart evolving of each one within the current month.

Awesome-Books

In this project, we built a basic website that allows users to add/remove books from a list. We achieved that by using JavaScript objects and arrays.

Portfolio-setup-and-mobile-version-skeleton

For this repository, I've created html templates and styling files in order to built a responsive portfolio , which can help to easy explorate profiles from differents devices.

Jane-Street-Market-Prediction

In this project, Jane Street which is a quantitative trading company ,challenged us to build our own quantitative trading model to maximize returns using market data from a major global stock exchange. Next, they’ll test the predictiveness of our models against future market returns.

Jupyter Notebook

Riiid-Answer-Correctness-Prediction

Kaggle competition, which challenge us to create algorithms for "Knowledge Tracing," the modeling of student knowledge over time. The goal is to accurately predict how students will perform on future interactions. We had pair our machine learning skills using Riiid’s EdNet data to get an AUC of 0.738 in private leaderboard .

Jupyter Notebook

ASHRAE---Great-Energy-Predictor-III

Develop accurate models for the global association Ashrae of metered building energy usage in the following areas: chilled water, electric, hot water, and steam meters. The data comes from over 1,000 buildings over a three-year timeframe.

Jupyter Notebook