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Solve classical computer vision topic, image recognition, with simplest method, tiny images and KNN(K Nearest Neighbor) classification, and then move forward to the state-of-the-art techniques, bags of quantized local features and linear classifiers learned by SVC(support vector classifier).
Apple Stock Price Forecasting using Sentiment Analysis
An end-to-end plagiarism classification model, deployed to SageMaker.
Text classification with Machine Learning and Mealpy
The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset
Machine learning model Visualizer in web using streamlit
Heart disease describes a range of conditions that affect your heart. Diseases under the heart disease umbrella include blood vessel diseases, such as coronary artery disease, heart rhythm problems (arrhythmia), and heart defects you’re born with (congenital heart defects), among others.
Heart disease describes a range of conditions that affect your heart. Diseases under the heart disease umbrella include blood vessel diseases, such as coronary artery disease, heart rhythm problems (arrhythmia), and heart defects you’re born with (congenital heart defects), among others.
Predicting house prices can help determine the selling price of a house in a particular region and can help people find the right time to buy a home.
I participated in the Titanic ML competition where I used machine learning to create a model to predict which passengers survived the Titanic shipwreck.
Repo on how to install and use thundersvm.
This is a small project to classify the GTZAN dataset by applying multiple algorithms for training the models.
This is a text classification for classifying the SMS as either spam message or non-spam message using Natural Language Processing.
Determining movie genres based on synopses, using various NLP methods.
Classification Machine Learning project
Predict whether a Mammogram Mass is Benign or Malignant.
Scraping data through Instagram and using the data to build a predictive model
This repository consists of programming projects of my pattern recognition course in which I used libraries like sklearn, Keras, Tensorflow, etc. Also, I am working on MNIST dataset in these projects and using support vector, probabilistic generative model, neural network, etc as learning methods.
Deep-learning is hard bro !, so made a binary classifier in machine learning that uses HSV Color Space to Look out for Features
Sentiment analysis of kinopoisk (https://www.kinopoisk.ru/) reviews. For analysis i used: classification methods (random forest, svc, k-neighbors) neural networks (lstm, mlp).
Using past Sport (Cricket) data to predict next win for Team India, in any format of the cricket.
NLP Classification and Clustering with spam SMS dataset
Projects for my Data Analytics class
This is in regard to algorithmic trading bot with the use of machine learning to predict potential returns and actual returns.
Udacity Data Scientist Nanodegree Project - Employ supervised algorithms to accurately model individuals income
Objective: To find if a given cancer specimen is malignant or benign using supervised machine learning algorithm- SVM (support vector machine)
Credit Card Fraud Detection
Employee-Absenteeism-Project-Work
A Flask web app which predicts whether it will rain tomorrow or not.
Predicting the risk of a person developing the coronary heart disease in 10 years using Machine Learning models.
Over the years, the company has collected basic bank details and gathered a lot of credit-related information. The management wants to build an intelligent system to segregate the people into credit score brackets to reduce the manual efforts.. You are hired as a data scientist to build a machine learning model that can classify the credit score.
GridSearchCV For Model optimization
Prevendo a postura usando traços de personalidade
This python project explains how to implement sentiment analysis using machine learning (SVM) on amazon Alexa reviews dataset.
This model predicts the Diabetes by using the Logistic Regression or SVC with using the Flask app