nikhilavalivarthi Goto Github PK

an-effective-and-decentralized-energy-transmission-system-for-developing-smart-villages

deeplearningforaudiowithpython

Code and slides for the "Deep Learning (For Audio) With Python" course on TheSoundOfAI Youtube channel.

forecasting-covid-19-time-series-data

instacart-market-basket-analysis

machine-learning

This repository consists of some of the algorithms covering simple topics to complex topics in Machine Learning.

machine-learning-projects

Various projects in Linear Regression, Logistic Regression, k Nearest Neighbors, Decision Trees, Random Forests, SVM

multi-layer-percepton

nikhilavalivarthi

Config files for my GitHub profile.

performance-evaluation-on-image-enhancement-techniques-for-underwater-images

In this paper, I would explain a few best approaches along with their experimental comparisons where the outcomes could give a broad idea on implementing the methods along with the submerged conditions they are specified to use.

pnemonia-detection-usingtransfer-learning

neumonia is an infection that inflames the air sacs in one or both lungs. The air sacs may fill with fluid or pus (purulent material), causing cough with phlegm or pus, fever, chills, and difficulty breathing. A variety of organisms, including bacteria, viruses and fungi, can cause pneumonia. Chest X-ray, blood tests, and culture of the sputum may help confirm the diagnosis. The disease may be classified by where it was acquired, such as community- or hospital-acquired or healthcare-associated pneumonia. ## Dataset description > The dataset is organized into 3 folders (train, test, val) and contains subfolders for each image category (Pneumonia/Normal). There are 5,863 X-Ray images (JPEG) and 2 categories (Pneumonia/Normal). Chest X-ray images (anterior-posterior) were selected from retrospective cohorts of pediatric patients of one to five years old from Guangzhou Women and Children’s Medical Center, Guangzhou. All chest X-ray imaging was performed as part of patients’ routine clinical care. For the analysis of chest x-ray images, all chest radiographs were initially screened for quality control by removing all low quality or unreadable scans. The diagnoses for the images were then graded by two expert physicians before being cleared for training the AI system. In order to account for any grading errors, the evaluation set was also checked by a third expert.

radial-basis-function-nn

self-organizing-map

sparkstreaming