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A New, Interactive Approach to Learning Data Science
Nudity/pornography detection using deeplearning. This model is trained using pretrained VGG-16. To know more about this check the readme file below
ML-powered Loan-Marketer Customer Filtering Engine
This repository is a related to all about Deep Learning - an A-Z guide to the world of Data Science. This supplement contains the implementation of algorithms, statistical methods and techniques (in Python)
Designing your first machine learning pipeline with few lines of codes using Orchest. You will learn to preprocess the data, train the machine learning model, and evaluate the results.
Malaria is a serious global health problem that affects millions of people each year. One of the challenges in diagnosing malaria is identifying infected cells from microscopic images of blood smears. Convolutional Neural Networks (CNNs) are a type of deep learning algorithm that have been used for image classification tasks etc
This nuget package is designed to help you easily identify and detect profanity or bad words within a given sentence or string. It works under a simple binary classifier that has been built and trained using ML.NET for accurate and efficient detection of inappropriate language.
Concrete cracking is a major issue in Bridge Engineering. Detection of cracks facilitates the design, construction and maintenance of bridges effectively.
Concrete cracking is a major issue in Bridge Engineering. Detection of cracks facilitates the design, construction and maintenance of bridges effectively.
Classification of two varients of rice - Osmancik, and Cammeo using machine learning
This project demonstrates the implementation of the Perceptron algorithm for binary classification tasks. It includes various advanced features such as data augmentation, feature engineering, and deep learning techniques to enhance model performance and robustness.
Text Classification Problem : Wrote a module to classify Amazon-Product Reviews as favourable/unfavourable. Achieved accuracy of 78% and an F1 score of .81 using Logistic Regression on a test-train split of 20%, where total records were around 50000.
TitanicClassification.py file contains project based on binary classification. The dataset comprises of data related to passengers and binary value of whether they survived or not.
The model is trained on the dataset from kaggle. used CNNs for training model. Has a accuracy of 97%.
In this we trained a model to detect if there is a tumor in the brain image given to the model. Meaning a model for binary class with an accuracy of above 90 for same and cross validation.
The dataset for this competition (both train and test) was generated from a deep learning model trained on the Pulsar Classification.
Бинарная классификация пользователей образовательной платформы Stepic на тех, кто скорее всего пройдет курс до конца и тех, кто скорее всего покинет платформу. Модель способна давать предсказания по анализу поведения юзеров на сайте за первые 3 дня
This project was built within 24h by the team Augusteam for the DevHacks 2022 Climate Change hackathon sponsored by Systematic and it won the third place worth 500€
Can we predict how long a patient will be in a hospital with a fair comparison on gender, race and health service areas?
Used Machine Learning to create a cryptocurrency classification system for my investment banking client who is interested in offering cryptocurrencies for its customers.
The goal of the project is to build a predictive model using machine learning concepts to predict customer attrition for a telecom service company.
Implementing a model that can verify if two images belongs to same personality or not. Answer the question "Is this the claimed person?" It is a 1:1 matching problem i.e. given a face your task is to compare the candidate face to another and verify whether it is a match or not. My custom CNN model has achieved marvelous performance on the dataset.
DECISION TREE CLASSIFIER - HYPER PARAMETER TUNING - Binary Classification
Predict whether a customer will default in the future
Individual projects done for the Data Science class
A model for binary classification of credit card data as fraudulent or legitimate
A classifier that can predict whether a passenger can survive the sinking of the Titanic
Models Breast Cancer data to make predictions