An Image Classification Model trained on 6000+ images of various plants. When an image is uploaded, it returns whether the plant is poisonous or not. Tri-Valley Hacks 2023 project.
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Jul 9, 2023 - Jupyter Notebook
An Image Classification Model trained on 6000+ images of various plants. When an image is uploaded, it returns whether the plant is poisonous or not. Tri-Valley Hacks 2023 project.
Diabetes Prediction using Machine Learning
The aim is to build a predictive model that can accurately classify whether the employee is likely to leave or the employee is likely to stay in the company. This allows companies to take proactive measures, such as improving working conditions, offering promotions, or addressing dissatisfaction, to retain valuable employees.
Machine Learning Model for Leaf Disease Detection
LyriGenesis is an Introduction to Artificial Intelligence (AI) Final Project. This is an AI model that takes a word or phrase from a user and uses it to generate song lyrics whose length is also based on another input by the user.
Machine Learning Model for Predicting Personality Traits
This Machine Learning Model Predict behavior to retain customers of a credit card services.
This is a Supervised Learning Model which predicts the Price of Real Estate in Madrid, Spain.
Repository which consists different code snippets and projects for my personal lessons recorded at the University of San Francisco in during learning of the Machine Learning.
ЭМИИА | EMIIA | КОГНИТИВНАЯ РАДИООПТИКА | COGNITIVE RADIO OPTICS | РАДИООПТИКА | RADIO OPTICS
Deep learning model and code for Toxic Comments Classification Challenge on Kaggle. Simple framework for similar competitions.
A method for predicting NAG interacting residues in a protein from its primary sequence
Building an ML model for detecting if a patient is COVID-19 positive or not. Based on dataset: https://www.kaggle.com/datasets/andyczhao/covidx-cxr2
Splitting the advertising data (advertising.csv) into training and testing data sets, then choosing and training a classification machine learning algorithm; Getting the accuracy of the ML model; Using feature engineering skills to create new features and improve my ML model;
📊 [ML] Classification Problem Solution: Guessing the type of a corrupted file
The credit card fraud detection model employs a Random Forest Classifier, a robust ensemble learning technique. It analyzes various transaction features to accurately identify fraudulent activities, leveraging the collective decision-making of multiple decision trees to enhance detection accuracy and resilience against data imbalances.
Implementation of Power Law Graph Transformer for Machine Translation and Representation Learning.
Machine Learning Model for Star Classification
Pipeline Classifier of Messages
Plasma cell-free DNA hydroxymethylomes discriminate disease state in EGFR-mutant non-small cell lung cancer.
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