ruhiawasthi Goto Github PK

-data-structures-and-algorithms

DSA CODE

coursera

This Repository Contains Some Codes And Project Of Coursera

deepeshgarg09.github.io

expense-tracker

farmo-consultant

Artificial Intelligence (AI) based Crop Recommendation system is desired for providing suggestions for all the crops which may increase profitability of the farmers. The system may consider parameters of good agricultural practices. Obtain soil type, water requirement / availability, seasonal parameters (temperature ranges, humidity, etc.) along with location and advise the best crops suitable along with what is required (quality / quantity of seeds, fertilizers,etc), duration of cultivation, demand, cost of cultivation and expected revenues / profits.

front-end-hackathon-resources

This repository contains the Code Of Conduct, Rules as well as Event Slides and Material for our very first event, i.e. Front End Hackathon.

fullstackproject

hiring-without-whiteboards

⭐️ Companies that don't have a broken hiring process

namaste-react

news-classifier

Develop a News Aggregator Web Application with a Database serving as the Backend.

notes-app

notes_backend

project--finding-donors-with-charityml-

In this project, you will employ several supervised algorithms of your choice to accurately model individuals' income using data collected from the 1994 U.S. Census. You will then choose the best candidate algorithm from preliminary results and further optimize this algorithm to best model the data. Your goal with this implementation is to construct a model that accurately predicts whether an individual makes more than $50,000. This sort of task can arise in a non-profit setting, where organizations survive on donations. Understanding an individual's income can help a non-profit better understand how large of a donation to request, or whether or not they should reach out to begin with. While it can be difficult to determine an individual's general income bracket directly from public sources, we can (as we will see) infer this value from other publically available features. The dataset for this project originates from the UCI Machine Learning Repository. The datset was donated by Ron Kohavi and Barry Becker, after being published in the article "Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid". You can find the article by Ron Kohavi online. The data we investigate here consists of small changes to the original dataset, such as removing the 'fnlwgt' feature and records with missing or ill-formatted entries.

python

This Repository Contains Some Python Code.

searching-algorithms

This repository contains the approach for different sorting algorithms.

sims

smart_inventory_frontend

smartdoc

sorting-algorithms

udacity--introduction-to-machine-learning-with-tensorflow

This Repository Contains Notebooks Of Projects And Mini-Projects From Udacity Nanodegree : Introduction To Machine Learning With Tensorflow