categorizing news: fake or not

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

Repo on how to install and use thundersvm.

A Flask web app which predicts whether it will rain tomorrow or not.

I participated in the Titanic ML competition where I used machine learning to create a model to predict which passengers survived the Titanic shipwreck.

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.

This is in regard to algorithmic trading bot with the use of machine learning to predict potential returns and actual returns.

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.

Using past Sport (Cricket) data to predict next win for Team India, in any format of the cricket.

This project demonstrates how to create a sentiment analysis and machine learning model on the IMDB dataset

This is a small project to classify the GTZAN dataset by applying multiple algorithms for training the models.

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.

Objective: To find if a given cancer specimen is malignant or benign using supervised machine learning algorithm- SVM (support vector machine)

Scraping data through Instagram and using the data to build a predictive model

This is a text classification for classifying the SMS as either spam message or non-spam message using Natural Language Processing.

Credit Card Fraud Detection

Determining movie genres based on synopses, using various NLP methods.

Employee-Absenteeism-Project-Work

Sentiment analysis of kinopoisk (https://www.kinopoisk.ru/) reviews. For analysis i used: classification methods (random forest, svc, k-neighbors) neural networks (lstm, mlp).

Classification Machine Learning project

Udacity Data Scientist Nanodegree Project - Employ supervised algorithms to accurately model individuals income

Predict whether a Mammogram Mass is Benign or Malignant.

Projects for my Data Analytics class

NLP Classification and Clustering with spam SMS dataset

Different classification algorithms to determine whether or not an individual from the Pima group will have type 2 diabetes