Classifying remote sensing data with random forest

Jupyter notebook: GRASS GIS 8 and processing of multitemporal EO data

A Machine learning binary classification project using sklearn based on Covid19 symptoms dataset.

Location information about commuter activities is vital for planning for travel disruptions and infrastructural development. The Mobility Sensing Project aims to find innovative and novel ways to identify travel patterns from GPS data and other multi-sensory data collected in smartphones. This will be transformative to provide personalised trave…

Forecasting stock prices of S&P500 using RandomForest and LSTM (Pytorch)

Code templates for data prep and different ML algorithms in Python.

HANDWRITTEN DIGIT RECOGNITION USING ML IN PYTHON WITH THE HELP OF RANDOM FOREST CLASSIFIER

Explore and predict the used car price by building the machine learning model based on the existing data. Then examining the model between the actual price and the predicted price.

Digit recognizer with our own dataset

Heart disease classification project with different models (LogisticRegression, KNeighboursClassifier, RandomForestClassifier) and detailed reports.

An Oil Detection App built with RandomForestClassifier, Heroku, plotly, and Flask

Note : This Repository consists files of the Project -Detecting fraud for transactions in a payment gateway - Ind Avenue which was held as a Mid Term Hackathon Competition a part of my PGP Data Science Program @ Insofe.

Predict the activity category of a human.

Competición Kaggle: analizar clientes fugados y activos y entrenar un sistema que sea capaz de predecir si un cliente se ha fugado.

Create a machine learning model to predict if the policyholder will file a claim in the next 6 months or not based on the set of car and policy features.

Heart disease detection using Machine Learning

Advanced Machine Learning