Pinned Repositories
amazon-sagemaker-examples
Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker
amazon-sagemaker-satellite-imagery-segmentation
amazon-sagemaker-tensorflow-object-detection-api
Train and deploy models using TensorFlow 2 with the Object Detection API on Amazon SageMaker
awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
Awesome_Satellite_Benchmark_Datasets
Supplementary material for our paper "THERE IS NO DATA LIKE MORE DATA" is provided.
azure-devops-docs
This repo is the home of the official Azure DevOps documentation for Microsoft. GitHub Issues filed in this repository should be for problems with the documentation.
bhuvana_site
My personal website
Bite-Sized-Learning-Python
Classical-Least-Squares-Method-for-Quantitative-Spectral-Analysis
Classical Least Squares method implementation with Python
Customer-Feedback-Sentiment-Analysis-using-LSTM
A Python Flask Based Web App to classify customer reviews sentiments using LSTM RNN
dhananjay-nalawade's Repositories
dhananjay-nalawade/Object-Classification-on-CIFAR-10-Dataset
dhananjay-nalawade/Spam-classification
dhananjay-nalawade/NDVI-Viewer
Monitor Vegetation Health by Viewing & Comparing NDVI Values & Satellite Images On The Fly!
dhananjay-nalawade/deeplearning-cnn
A Convolutional Neural Network (CNN)
dhananjay-nalawade/EDAA
dhananjay-nalawade/neurolab-pyspark
dhananjay-nalawade/DataScienceR
a curated list of R tutorials for Data Science, NLP and Machine Learning
dhananjay-nalawade/dataset1
YouTube
dhananjay-nalawade/Hands-on-Exploratory-Data-Analysis-with-Python
Hands-on Exploratory Data Analysis with Python, published by Packt
dhananjay-nalawade/dhananjay-nalawade
Config files for my GitHub profile.
dhananjay-nalawade/python-sample-vscode-flask-tutorial
Sample code for the Flask tutorial in the VS Code documentation
dhananjay-nalawade/workload-discovery-on-aws
Workload Discovery on AWS is a solution to visualize AWS Cloud workloads. With it you can build, customize, and share architecture diagrams of your workloads based on live data from AWS. The solution maintains an inventory of the AWS resources across your accounts and regions, mapping their relationships and displaying them in the user interface.
dhananjay-nalawade/raster4ml
A geospatial raster processing library for machine learning
dhananjay-nalawade/Unmixing_Tutorial_IEEE_IADF
Codes and data for Unmixing
dhananjay-nalawade/vprofile-project
for DevOps tools
dhananjay-nalawade/pipelines-python-django
Sample Python Django application for Azure Pipelines docs
dhananjay-nalawade/Satellite-Imagery-Datasets-Containing-Ships
A list of radar and optical satellite datasets for ship detection, classification, semantic segmentation and instance segmentation tasks.
dhananjay-nalawade/LUIT-angular-app
for trial
dhananjay-nalawade/amazon-sagemaker-tensorflow-object-detection-api
Train and deploy models using TensorFlow 2 with the Object Detection API on Amazon SageMaker
dhananjay-nalawade/Enhancement_of_MODIS_NIDVI
Enhancement of MODIS NIDVI to 10m resolution using U-Net
dhananjay-nalawade/serverless-coffee-workshop
This is the repo for Serverlesspresso workshop. Questions? Contact @jbesw or @benjamin_l_s on GitHub or Twitter.
dhananjay-nalawade/sweet_potato_detection
An experiment of sweet potato detection using Keras implemented Single Shot MultiBox Detector
dhananjay-nalawade/DE-Projects
Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development.
dhananjay-nalawade/MS2A-Net
Hyperspectral image clustering
dhananjay-nalawade/DLPan-Toolbox
DLPan Toolbox for Pansharpening
dhananjay-nalawade/sample_project
dhananjay-nalawade/investment_prediction
dhananjay-nalawade/satellite-image-deep-learning
Resources for deep learning with satellite & aerial imagery
dhananjay-nalawade/Machine-Learning
Here you will find all the concepts related to Machine Learning.
dhananjay-nalawade/sagemaker-inference-toolkit
Serve machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.