This is the material for Jose Portilla's Spark and Python for Big Data and ML course.
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Updated
Aug 4, 2024 - Jupyter Notebook
This is the material for Jose Portilla's Spark and Python for Big Data and ML course.
By Analyzing the dataset through Machine and Deep learning models we have to classify whether a person has heart disease or not.
Our project utilizes machine learning models to predict cardiovascular diseases (CVDs) by analyzing diverse datasets and exploring 14 different algorithms. The aim is to enable early detection, personalized interventions, and improved healthcare outcomes.
Have build a predictive model to determine the likelihood of survival for passengers on the Titanic using data science techniques in Python.
Credit scoring is a crucial task in financial institutions to assess the creditworthiness of individuals or businesses. This project focuses on building classification models to predict credit scores based on various features such as income, debt, and credit history.
Multi-Label Classifier with ETL, NLP, Sklearn, Flask, + Plotly
A simple sentiment analysis using SGD and LinearSVC for Amazon Reviews
Cuisine Predictor takes a list of ingredients from a user and attempts to predict the type of cuisine and similar meals
A loan prediction modes
Cuisine Predictor is a python based tool which uses LinearSVC and kNeighborsClassifier to predict the cuisine and similar dishes from Yummly catlog.
🖼️ Text2Meme is a Meme Classification Experiment based on Caption Text (Implemented as a Discord Bot)
AI Biceps Curl Counter
Build a machine learning classifier that knows whether President Trump or Prime Minister Trudeau is tweeting!
A project on classification of GitHub readme sections using Machine Learning
A Machine Learning project made in Python used to classify unit text to a specified topic. Employed by Auburn University at Montgomery part-time while creating the application and finishing up my final university semester
There are three classes InfoTheory, CompVis and Math. These can occur in any combination, so an article could be all three at once, two, one or none. The job is to build text classifiers that predict each of these three classes individually using the Abstract field.
A project to predict if customer churns or not using ML algorithms
Building machine learning classifiers to label tweets as "Hate Speech", "Offensive Language", or "Neither"
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