sneharaoganta

alarm

Android_Malware_Analysis

Static and Dynamic Analysis of android malware using various different machine learning algorithms

CSS-art

Creating simple and cute art using purely CSS

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

Depth_ESTIMATION_MML

Spatiotemporal Depth Estimation using Monocular Cameras using Kitty Dataset.

FaceMaskDetector

A Face Mask Detector created using features from TensorFlow, OpenCV, Keras, and MobileNets on real video streams. This model could be used in real-time applications during the pandemic as well.

Gender-Recognition-By-Audio-Data

Gender Classification using different algorithms for classification i.e K Nearest Neighbor, Naive Bayes, Decision Tree, Random Forest, XgBoost, Support Vector Machine and Neural Network i.e. MLP classifier to generate results.

Personality-Prediction-System

Use of data mining concepts and python data science libraries for simple demonstration to analyse and classify personalities of a given set of people or an individual.

Recipe_Generator

Recipe Generator: RNN Models used to train the dataset to learn basics concepts of english and generate different parts of a recipe.

WhatsAppAnimatedStickerMaker

Sticker making Android App built in Android Studio using Kotlin.

sneharaoganta/Android_Malware_Analysis

Static and Dynamic Analysis of android malware using various different machine learning algorithms

sneharaoganta/CSS-art

Creating simple and cute art using purely CSS

sneharaoganta/Depth_ESTIMATION_MML

Spatiotemporal Depth Estimation using Monocular Cameras using Kitty Dataset.

sneharaoganta/FaceMaskDetector

A Face Mask Detector created using features from TensorFlow, OpenCV, Keras, and MobileNets on real video streams. This model could be used in real-time applications during the pandemic as well.

sneharaoganta/Gender-Recognition-By-Audio-Data

Gender Classification using different algorithms for classification i.e K Nearest Neighbor, Naive Bayes, Decision Tree, Random Forest, XgBoost, Support Vector Machine and Neural Network i.e. MLP classifier to generate results.

sneharaoganta/Personality-Prediction-System

Use of data mining concepts and python data science libraries for simple demonstration to analyse and classify personalities of a given set of people or an individual.

sneharaoganta/Recipe_Generator

Recipe Generator: RNN Models used to train the dataset to learn basics concepts of english and generate different parts of a recipe.

sneharaoganta/WhatsAppAnimatedStickerMaker

Sticker making Android App built in Android Studio using Kotlin.

sneharaoganta/alarm

sneharaoganta/deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

sneharaoganta/IPMP1921

sneharaoganta/NASAviewer

sneharaoganta/oneAPI-samples

Samples for Intel oneAPI toolkits

sneharaoganta/SNEHA_RAO

sneharaoganta/SOP-Task-0

sneharaoganta/SOP_Task1

The repository for the initial task of the Spider Orientation Programme (SOP)

sneharaoganta/TitanicDataset

A titanic passenger survival dataset is analyzed and trained using Tensorflow

sneharaoganta/trial

sneharaoganta/trial2

sneharaoganta/VideoEditor

FFmpeg is a powerful multimedia framework which allows us to decode, encode, transcode, stream, filter and play most of the media content available now. With the help of these tools, you can develop and application that can manipulate any form of media to the desired output. Sky is not the limit when using FFmpeg. I prefer FFmpeg-all which is a Bible for FFmpeg but it is difficult to read if you do not know what you are looking for. To make it easy, I will summarise the basics of video manipulations using FFmpeg which, then you can use in your own applications or libraries that you are working on. I have developed a simple library that enables you to trim and crop a video, additionally you can compress any video and convert it into any format that you desire.