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machine learning practitioner, android and python
Machine Learning Telecom Churn Model
An NLP analysis on the impact of Star Trek: The Next Generation's character spoken lines and how it affects the rating of the episode.
This repository is about using multivariate linear regression in airfoil self noise using python. It will help you to use different types of commands of different types of libraries in python.
A machine learning project that predicts the future price of Ethereum (ETH) using the price data gathered from coincodex.com.
website forcasting bukit darmo property
Reddit Post Flair Detector for r/india Subreddit
Website Prediksi Pembuatan beer Menggunakan Beberapa Model
utilize the sklearn library to train models on a set of data and use to make predictions
Using ML methods, develop a data analytics-based strategy to help classify if prospective borrowers would be a risk to a bank. With the use of predictive modeling, a bank could determine whether an applicant is approved or rejected for a loan by analyzing their credit risk. (Final Group Project for CIND119)
Predict bike sharing demand using multiple linear regression model.
International Sports Events and Repression in Autocracies. Statistical Analysis with Python
Supervised learning model that predicts whether an individual makes more than $50000 per year (accuracy score of 0.87) .
Simple API, built with FAST API, with advanced linear regression of California home prices.
Build end-to-end DL pipeline for computer vision (Image classification) for “Chest Disease Classification from Chest CT Scan Images” and deploy Flask web app to AWS EC2 with Docker and CI/CD tool: Jenkins
A lung cancer decision tree is a type of machine learning model that can predict the likelihood of a patient having lung cancer based on various features such as smoking habits, age, and symptoms such as yellow fingers, anxiety, fatigue, etc.
This repository tries to predict some NBA awards with machine learning
The goal of this project is to help a mail-order sales company in Germany to identify segments of the population that form the core customer base. These segments can then be used to direct marketing campaigns towards audiences that should bring high expected returns.
UCLA Computer Science Summer Institute; CS97 - Introduction to Data Science
Clustering Amazon review data around 6M users using Kmeans and Dbscan algorithm.
This report is generated of what cryptocurrencies are available on the trading market and how they can be grouped using classification.
Testing different machine learning methods on advertising dataset. With a simple RESTAPI using flask
Iniciando estudos sobre o dataset de distribuição de bolsas do ProUni