Pinned Repositories
100-Days-of-ML
Records 100 days of Machine learning and Deep learning algorithms in Python
3D-point-cloud-Segmentation-and-Clustering-with-Python
Automating the Python Cloud Segmentation and 3D shape detection Using multi-order ransac and unsupervised clustering DBSCAN
A-star-search-Algorithm
Basic_C_Programs
Basic C Programs
BoschGLM50C
Deep-Learning-Networks-with-PyTorch
The course will teach you how to develop deep learning models using Pytorch. The course will start with Pytorch's tensors and Automatic differentiation package. Then each section will cover different models starting off with fundamentals such as Linear Regression, and logistic/softmax regression. Followed by Feedforward deep neural networks, the role of different activation functions, normalization and dropout layers. Then Convolutional Neural Networks and Transfer learning will be covered. Finally, several other Deep learning methods will be covered. Learning Outcomes: After completing this course, learners will be able to: 1. explain and apply their knowledge of Deep Neural Networks and related machine learning methods 2. know how to use Python libraries such as PyTorch for Deep Learning applications 3.build Deep Neural Networks using PyTorch
Lidar_Obstacle_detection_Udacity
Implemented RANSAC Segmentation and Euclidean Clustering algorithms using lidar.
Python_Basic_Programs
Python programming examples
Tcp_Client_Server_Architecture
Implemented the TCP(Client and Server Architecture) and collected data from the sensor to perform the temperature and humidity detection.
YoloV3_DeepSort
Real-time Multi-person tracker using YOLO v3 and deep_sort with tensorflow
prudhvirajstark's Repositories
prudhvirajstark/100-Days-of-ML
Records 100 days of Machine learning and Deep learning algorithms in Python
prudhvirajstark/A-star-search-Algorithm
prudhvirajstark/Basic_C_Programs
Basic C Programs
prudhvirajstark/Deep-Learning-Networks-with-PyTorch
The course will teach you how to develop deep learning models using Pytorch. The course will start with Pytorch's tensors and Automatic differentiation package. Then each section will cover different models starting off with fundamentals such as Linear Regression, and logistic/softmax regression. Followed by Feedforward deep neural networks, the role of different activation functions, normalization and dropout layers. Then Convolutional Neural Networks and Transfer learning will be covered. Finally, several other Deep learning methods will be covered. Learning Outcomes: After completing this course, learners will be able to: 1. explain and apply their knowledge of Deep Neural Networks and related machine learning methods 2. know how to use Python libraries such as PyTorch for Deep Learning applications 3.build Deep Neural Networks using PyTorch
prudhvirajstark/Python_Basic_Programs
Python programming examples
prudhvirajstark/Tcp_Client_Server_Architecture
Implemented the TCP(Client and Server Architecture) and collected data from the sensor to perform the temperature and humidity detection.
prudhvirajstark/Camera-based2D-Feature-Tracking
this project builds a collision detection system and build the feature tracking part.
prudhvirajstark/Coursera-Cerificates
List of all the Coursera Certificates
prudhvirajstark/Cpp-snippets-Design-patterns
prudhvirajstark/CV
prudhvirajstark/Daily-Coding-DS-ALGO-Practice
A repo for bringing all interview and competative programming question under one repo
prudhvirajstark/DeepLearningIoT
This repository contains files related to IoT With Deep learning in Python
prudhvirajstark/Elevator-System
Implemented single elevator system with specific floor the user wants to take the elevator, and the requests to specific floor to stop when the user is inside the elevator,
prudhvirajstark/FastAPI-React-Redis-Microservices
This repo inlcudes fastapi, redis and react which creates a inventory and payment microservices
prudhvirajstark/first-contributions
🚀✨ Help beginners to contribute to open source projects
prudhvirajstark/go-graceful-restapi-server
go-graceful-restapi-server is a simple yet robust RESTful API web server built with Go, featuring graceful shutdown capabilities for seamless operation.
prudhvirajstark/go-notes-rest-api
A lightweight Go (Golang) API service designed for managing personal notes. It provides a secure authentication system for users to sign up, log in, and access their notes securely.
prudhvirajstark/grpc-task-manager-golang
a gRPC-based task management system
prudhvirajstark/homomorphic-encryption-MLops
prudhvirajstark/Manipal
COntains IOT Lab arduino/Raspberry
prudhvirajstark/Microservice_SOLID
Home Automation Microservice Prototype is a simple demonstration of modularity and separation of concerns using Go programming language
prudhvirajstark/minimal-Jekyll
Customized Minimal is a Jekyll theme for GitHub Pages
prudhvirajstark/Optimize-image-duplicates
This is a python repository that detects and remove all similar-looking images from the datasets.
prudhvirajstark/portfolio
Portfolio
prudhvirajstark/prudhvirajstark
A short description about me and my interests.
prudhvirajstark/python-parquet-example
Example usage of python with parquet for IoT data storage and analytics
prudhvirajstark/pytorch-golang-plant-system
This repository contains the source code for a Smart Plant Watering System, an automated solution for monitoring and managing the watering needs of potted plants. The system integrates deep learning, microservices in Golang, and databases to create an intelligent and efficient plant care solution.
prudhvirajstark/Simple-PointCloud-Data-PCL-
The main purpose of this personal project was to provide an educational and skill challenge in C++, to myself.
prudhvirajstark/THE-SPARKS-FOUNDATION
prudhvirajstark/Twitter-data-pipeline-hashtag
This is a data pipeline for twitter (ETL) Using python and tweepy