90daysofdevops

This repository is a Challenge for the DevOps Community to get stronger in DevOps. This challenge starts on the 1st January 2023 and in the next 90 Days we promise ourselves to become better at DevOps. The reason for making this Public is so that others can learn from the community and help each other grow.

alexa-speaks-ai

It is capable of voice interaction, music playback, making to-do lists, setting alarms, streaming podcasts, playing audiobooks, and providing weather, traffic, sports, and other real-time information, such as news. Alexa can also control several smart devices using itself as a home automation system.

alloys

amazon-alexa

In this project we will do sentiment analysis on Amazon-Alexa

ansible-projects

aws-node-http-api-project

aws-node-http-api-project for server less

competitive-codes-question-answer

devops

devopsdemo

devsecops-project

DevSecOps Project to setup Netflix clone on AWS using CICD, Security, Monitoring and GitOps

fake-news-detection-platform

flight-price-prediction

git

graphicsfuzz

A testing framework for automatically finding and simplifying bugs in graphics shader compilers.

imdb-sentiment-analysis

Classified the users movie review from IMDB and analyzed the sentiment of the users regarding the movie.

kubernetes-end-to-end-project

machine-learning-predictions

Machine Learning Prediction of Scores

motion-detector

mussis.github.io

netflix-movies-and-tv-shows-exploratory-analysis

This dataset consists of tv shows and movies available on Netflix as of 2019. The dataset is collected from Flixable which is a third-party Netflix search engine. In 2018, they released an interesting report which shows that the number of TV shows on Netflix has nearly tripled since 2010. The streaming service’s number of movies has decreased by more than 2,000 titles since 2010, while its number of TV shows has nearly tripled. It will be interesting to explore what all other insights can be obtained from the same dataset. Integrating this dataset with other external datasets such as IMDB ratings, rotten tomatoes can also provide many interesting findings.

netflix-shows-analysis

This dataset consists of tv shows and movies available on Netflix as of 2019. The dataset is collected from Flixable which is a third-party Netflix search engine. In 2018, they released an interesting report which shows that the number of TV shows on Netflix has nearly tripled since 2010. The streaming service’s number of movies has decreased by more than 2,000 titles since 2010, while its number of TV shows has nearly tripled. It will be interesting to explore what all other insights can be obtained from the same dataset. Integrating this dataset with other external datasets such as IMDB ratings, rotten tomatoes can also provide many interesting findings.

node-todo-cicd

rahul2812-creator

react_django_app

A demo app for React and Django Deployment

self-driving-car

terraform-projects

weather-api

web-scrap-nodes