kkaustubh0

100DaysOfCode

Analysis_of_Vowels_onset_Point_Based_Features

In this implementation, two features have been handcrafted based on vowel onset point of depressed and non-depressed speech signals for classification.

Calories_Burnt_Prediction_Using_XGBoost

In this project, we are using the XGBoost Regressor for predicting the amount of calories burnt during the exercise based on parameters like a person's age, height, weight, duration of exercise, heart rate, body temperature and so on. The dataset has been split into 9:1 and mean absolute error has been used as the evaluation metric.

Convolutions_Operations_Classifications

Convolutions

iNeuron_Data_Science_Assignments

kmeans_clustering

In this repository I have implemented segmentation of customers based on their spending scores and annual income using k-means clustering algorithm

Linear_Regression_Using_sklearn

In this repository, linear regression has been performed using sklearn on film_budget vs. worldwide_revenue data

openSMILE_based_Features_for_Depression_Classification

In this implementation, 88 dimensional openSMILE features have been extracted for the speech signal and have been used for classification of depressed and non-depressed speech using simple feed forward neural networks. Also these 88-dimesional feature vectors have been encoded to a smaller dimension using an autoencoder and classification is done.

Probability_Assignment

The repository consists of the following implementation in python

Resume-HTML

My Resume

kkaustubh0/100DaysOfCode

kkaustubh0/Analysis_of_Vowels_onset_Point_Based_Features

In this implementation, two features have been handcrafted based on vowel onset point of depressed and non-depressed speech signals for classification.

kkaustubh0/Calories_Burnt_Prediction_Using_XGBoost

In this project, we are using the XGBoost Regressor for predicting the amount of calories burnt during the exercise based on parameters like a person's age, height, weight, duration of exercise, heart rate, body temperature and so on. The dataset has been split into 9:1 and mean absolute error has been used as the evaluation metric.

kkaustubh0/Convolutions_Operations_Classifications

Convolutions

kkaustubh0/iNeuron_Data_Science_Assignments

kkaustubh0/kmeans_clustering

In this repository I have implemented segmentation of customers based on their spending scores and annual income using k-means clustering algorithm

kkaustubh0/Linear_Regression_Using_sklearn

In this repository, linear regression has been performed using sklearn on film_budget vs. worldwide_revenue data

kkaustubh0/openSMILE_based_Features_for_Depression_Classification

In this implementation, 88 dimensional openSMILE features have been extracted for the speech signal and have been used for classification of depressed and non-depressed speech using simple feed forward neural networks. Also these 88-dimesional feature vectors have been encoded to a smaller dimension using an autoencoder and classification is done.

kkaustubh0/Probability_Assignment

The repository consists of the following implementation in python

kkaustubh0/Resume-HTML

My Resume

kkaustubh0/Spectrograms

Here, we shall be visualising the spectrograms of two wav files and compare them using the library librosa in python.

kkaustubh0/Voice_Activity_Detector

Implementation of voice activity detector (Removing silences from the speech)