100-days-of-ml-code

100 Days of ML Coding

aditya-verma-youtube-playlist-code

This repo consists of aditya verma youtube channel code for different section.

algo_ds_notes

It is a repository that is a collection of algorithms and data structures with implementation in various languages.

amazon-sde-test-series

This repository includes all the interview preparation questions for Amazon SDE role

awesome-interview-questions

:octocat: A curated awesome list of lists of interview questions. Feel free to contribute! :mortar_board:

bitcoin-curriculum

Bitcoin Protocol Development Curriculum

competitive-programming

Hello Programmers :computer: , A one-stop Destination✏️✏️ for all your Competitive Programming Resources.📗📕 Refer CONTRIBUTING.md for contributions

data-structures-and-algorithms

Contains Implementation of selected Data Structures and Algorithms which are important for the interview preparations

dataset

Data for practice

dsa

Data structure and Algorithm (DSA) contributions

dsa-450

dynamic_programming_journey

Sharing my journey :purple_heart: of Dynamic Programming :dizzy: :fire: . This would not be possible without Aditya Verma's DP series :pray: :point_down: :point_down:

feature-engineering

flask-project

getting-a-gig

Guide for getting a gig as a tech student.

github-profile-page

github-readme-stats

:zap: Dynamically generated stats for your github readmes

github-readme-stats-1

github-slideshow

A robot powered training repository :robot:

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

harvardx-cs50w

CS50's Web Programming with Python and JavaScript

interview-prep

Everything you need to know to get the job

jenkins-docker-maven-java-webapp

kushal997-das

Kushal Das Portfolio

machine-learning

machine-learning-tutorials

machine learning and deep learning tutorials, articles and other resources

multiple-disease-prediction-system

A lot of analysis over existing systems in the health care industry considered only one disease at a time. For example, one system is used to analysediabetes, another is used to analyse diabetes retinopathy, and another system is used to predict heart disease. Maximum systems focus on a particular disease. When an organization wants to analyse their patient’s health reports then they have to deploy many models. The approach in the existing system is useful to analyse only particular diseases. In multiple diseases prediction system a user can analyse more than one disease on a single website. The user doesn’t need to traverse different places in order to predict whether he/she has a particular disease or not. In multiple diseases prediction system, the user needs to select the name of the particular disease, enter its parameters and just click on submit. The corresponding machine learning model will be invoked and it would predict the output and display it on the screen.

novatorem

Dynamic realtime profile ReadMe linked with spotify

novatorem-1

pentest-notes