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applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

applying-machine-learning-to-charity-donations

The goal of this project is to apply machine learning techniques on data collected for the KDD 98 competition to help a fictional charity organization identify people most likely to donate to their cause.

charity-donation

You have been hired to deliver actionable insight to support a client who is a national charitable organisation. The client seeks to use the results of a previous postcard mail solicitation for donations to improve outcome in the next campaign. You want to determine which of the individuals in their mailing database have characteristics similar to those of your most profitable donors. By soliciting only these people, your client can spend less money on the solicitation effort and more money on charitable concerns.

cors-anywhere

CORS Anywhere is a NodeJS reverse proxy which adds CORS headers to the proxied request.

data-analyst-skill-with-videos-in-2021

developer-roadmap

Roadmap to becoming a web developer in 2021

explainerdashboard

Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

exploratory-data-analysis---freecode-camp-2021-new-coder-survey

fastapi

Microservice creation and Machine Learning Model Deployment using FastAPI

gatsby-simplefolio

⚡️ A minimal Gatsby portfolio template for Developers

industry-machine-learning

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

jindukwentua

lazypredict

Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

loan-application

Analyzing the credit-worthiness of a borrower is an essential step in the loan-making process which has been going on for hundreds of years to varying degrees. Machine learning algorithms can be used to assist institutions in accurately predicting the riskiness of borrowers. We aim to apply a novel approach that uses feature engineering which will hopefully boost predictive power. The goal of this project is to determine whether a borrower will default on their loan, using both traditional features (salary, level of education, amount in account etc) and non-traditional features that will be used to determine if a customer is eligible for a loan or not.

my_portfolio

Attempt

nlp-tutorial

Natural Language Processing Tutorial for Deep Learning Researchers

node-crud-app

optimized-modified-getoldtweets3-omgot

GetOldTweets-Python is a project written in Python to mine old and backdated tweets, It bypasses some limitations/restrictions of the Twitter API. This Repo houses an improvement fork of the original GetOldTweets Library by [Jefferson Herique](https://github.com/Jefferson-Henrique/GetOldTweets-python). The improvement makes running this package on Windows OS seamless with Python 3.x.

portfolio-project

Portfolio Website

predicting-students-performance

public-apis

A collective list of free APIs for use in software and web development.

python-cheatsheet

Comprehensive Python Cheatsheet

randomforest-algorithm-on-a-dataset-

sga07_datasci-1

Stutern Projects

sga07_datasci-2

Contains all practice lab for Stutern data science course

sga07_datasciencetrack

This repository contains all practice labs, assignments and projects for Stutern Graduate Accelerator Program - Data Science Track

shooting-dataset

social-media-and-sentiment-analysis-the-past-2-nigerian-elections

Twitter undoubtedly contains a diverse range of political insight and commentary. But, to what extent is this representative of an electorate? Can we analyze political sentiment effectively enough to capture the voting intentions of a nation during an election campaign? In this present day, social media platforms are playing a vital role in influencing people’s sentiment in favor or against a government or an organization. Twitter-based data is not inherently a representative sample of society. However, opinion mining using machine learning techniques can categorize a tweet as positive, negative, and neutral in such a way that the election winner can be predicted almost quite accurately based on the ratio of positive tweets to the total tweet mentions. This project aims to identify and analyze public sentiments towards the top presidential candidates within the past 2 Nigerian elections, with the aim of determining their chances of being elected into the highest position of authority in Nigeria based on social media comments.

tableau

titanic

Titanic dataset