Tune Hyperparameters of Decision Tree with Grid Search

Tuning NN parameters from keras library with sklearn's grid search

This repository includes all the udacity deep learning project that i have worked on while i was taking this course

Hyperparameter tuning for text categorization using differential evolution

This repository contains a simple machine learning project build using Azure machine learning service

Neural Networks, Deep Learning, Computer Vision, Natural Language Processing, Python

Project for Deep Learning Nanodegree, unit 4 (Recurrent Neural Networks).

Analyze the performance of 7 optimizers by varying their learning rates

A ML model to classify mobile price range.

Applied several models (decision tree, logistic regression, random forest) to solve a classification problem on demographic data. Explored and compared model performance with hyperparameter tuning.

Used machine learning to create a model that predicts which passengers survived the Titanic shipwreck

In this problem statement, a sequence of genetic mutations and clinical evidences, i.e. descriptive texts as recorded by domain experts are used to classify the mutations to conclusive categories, to be used for diagnosis of the patient.

RTA severity predictor is an application which predicts the severity of road traffic accident, so as to pave the way for improving the safety level of road traffic.

Improving Machine Learning Performance by: feature engineering, oversampling and hyperparameter tuning

Building Machine Learning Models with hyperparameter tuning by training a dataset containing more than a million rows to accurately predict the taxi trip duration in New york city

Different types of supervised learning models used for classification problem. Included cross validation for finding hyperparameters whenever necessaruy.

Data Science Portfolio created for academic and personal projects.

Machine learning model using sklearn on pandas dataframe

Dog breed classification using AWS SageMaker