aditya-saxena-7 Goto Github PK

aditya-saxena-7.github.io

airlines-management-smart-system

Database Management Assignment 2nd Semester 2020-21

ars_cheetah.v2

Training the Half-Cheetah model to walk and run on the MUJOCO environment using the gym library. The model is trained using Augmented Random Search algorithm which reached the maximum award of +972 on the training episode.

astra

aws-live

convolutional_neural_network

Using Convolutional_Neural_Network for Image Classification on FashionMNIST and (Cats and Dogs) dataset

credit-risk-assessment-model-for-uae-s-commercial-banks-a-machine-learning-approach-dataset

Credit Risk Model on Machine learning and prediction

deep_neural_network

Deep Learning model for predicting and manipulating Traffic behavior (Data by Abu Dhabi Road Authority) and predicting chances of employees leaving a given company based on various parameters(Churn_Modelling)

detection-of-covid-19-from-chest-x-ray-images-using-cnns

The COVID-19 (coronavirus) is an ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus was first identified in mid-December 2019 in the Hubei province of Wuhan, China and by now has spread throughout the planet with more than 75.5 million confirmed cases and more than 1.67 million deaths. With limited number of COVID-19 test kits available in medical facilities, it is important to develop and implement an automatic detection system as an alternative diagnosis option for COVID-19 detection that can used on a commercial scale. Chest X-ray is the first imaging technique that plays an important role in the diagnosis of COVID-19 disease. Computer vision and deep learning techniques can help in determining COVID-19 virus with Chest X-ray Images. Due to the high availability of large-scale annotated image datasets, great success has been achieved using convolutional neural network for image analysis and classification. In this research, we have proposed a deep convolutional neural network trained on five open access datasets with binary output: Normal and Covid. The performance of the model is compared with four pre-trained convolutional neural networkbased models (COVID-Net, ResNet18, ResNet and MobileNet-V2) and it has been seen that the proposed model provides better accuracy on the validation set as compared to the other four pre-trained models. This research work provides promising results which can be further improvise and implement on a commercial scale.

face-and-motion-detection-using-opencv

Real-time face recognition project with OpenCV and Python. This project was made in consideration of use of Computer Vision in Retail Sector for Real Life Theft Prevention.

insectisides-pesticides-classifier-for-crop-production

In this notebook I will implement a deep learning model that can identify plant diseases, using the Pytorch framework, a Convolutional Neural Network (CNN) architecture. The goal is to detect different plant diseases by looking a picture. I'll train this image classifier to recognize the different plant diseases given an image. This can be implemented in a phone app called Digital Mandi that tells you the type of disease your camera is looking at. I will use the "Plant Village" dataset.

lithium-ion-battery-deep-neural-network-

"Lithium-Ion Battery Life Prediction Based on Initial Stage-Cycles Using Machine Learning"--Deep Neural Model

lithium-ion-battery-gradient-boosting-trees-

"Lithium-Ion Battery Life Prediction Based on Initial Stage-Cycles Using Machine Learning"-- Gradient Boosting Trees Model

lithium-ion-battery-kernel-pca-

"Lithium-Ion Battery Life Prediction Based on Initial Stage-Cycles Using Machine Learning"-- Kernel PCA Model

lithium-ion-battery-lda-

"Lithium-Ion Battery Life Prediction Based on Initial Stage-Cycles Using Machine Learning"--LDA Model

lithium-ion-battery-naive-bayes-

"Lithium-Ion Battery Life Prediction Based on Initial Stage-Cycles Using Machine Learning"--Naive Bayes Model

lithium-ion-battery-pca-

"Lithium-Ion Battery Life Prediction Based on Initial Stage-Cycles Using Machine Learning"--PCA Model

naive_bayes-unsupervised-

AI's Naive Bayes algorithm for accurately predicting a binary classification of a given dataset from Kaggle

openai-python

opensea-js

JavaScript SDK for the OpenSea marketplace. Let your users buy or sell cryptogoods on your own site!

rad

RAD: Reinforcement Learning with Augmented Data

retail-and-wholesale-prices-for-all-agri-commodities

social-distancing-analyser-covid-19

A social distancing analyzer AI tool to regulate social distancing protocol using video surveillance of CCTV cameras and drones. Social Distancing Analyser to prevent COVID19

social-distancing-using-computer-vision-post-covid-19-yolov3

Described an efficient and economic approach of using AI to create a safe environment in a manufacturing setup. Demonstrated approach to build a robust social distancing measurement algorithm using a mix of modern-day deep learning and classic projective geometry techniques.

stock-prediction-using-rnn

Stock Predicting Model using RNN during Bull Market

terraform

Terraform enables you to safely and predictably create, change, and improve infrastructure. It is an open source tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned.

upper_confidence_bound-for-multi-armed-bandit

Using the Upper_Confidence_bound to solve the famous advertisement campaign problem in Reinforcement learning to double the reward.

wordcount-project

Wordcount using Django framework