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πŸ‡»πŸ‡³πŸ‡ΈπŸ‡¬ Hi Folks! I'm David a.k.a PVHuwung

Awesome GCP Portfolio page views GitHub followers

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Hi there! πŸ‘‹

Here are some ideas to get you started:

#!/bin/bash

πŸ”­ currentJob=" Currently working at: Advance Intelligence Group"
🌱 learning=" Learning about: Cloud, Software, and AI"
πŸ”οΈ collaboration=" Innovative AI and App Projects"
πŸ’¬ askMeAbout=" API Development, Cloud, AI, and System Design"
πŸ“« howToReachMe=" linkedin.com/in/vn-phamviethung"
🏎️ pronouns=" He/Him"
πŸ€– funFact=" No Fun"

info="$currentJob\n$learning\n$collaboration\n$askMeAbout\n$howToReachMe\
n$pronouns\n$funFact"

echo -e "$info"
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Golang Python Cplusplus CSharp JavaScript TypeScript Java Rust Deno
HTML5 CSS3 Node.js Streamlit NextJS Github Gitlab Git Docker
AWS GoogleCloud MongoDB GraphQL Firebase FastAPI Supabase MySQL PostgreSQL
// Get to know more about me with some Golang
package main

import (
	"fmt"
	"reflect"
)

type PVHuwung struct {
	Pronouns     string
	Backend      []string
	Frontend     []string
	Database     []string
	CloudServer  []string
	Architecture ArchitectureInfo
	Challenge    []string
	AISkills     []string
	Company      string
}

type ArchitectureInfo struct {
	Patterns   []string
	Components []string
	Challenges []string
	Serverless []string
}

func main() {
	var PVHUWUNG = PVHuwung{
		Pronouns:    "He/Him",
		Company:   "Advance Intelligence Group",
		Backend:     []string{"Go", "Python", "Rust", "C++"},
		Frontend:    []string{"Typescript", "NextJS", "HTML", "CSS"},
		Database:    []string{"PostgreSQL", "DynamoDB", "Firebase", "Redis"},
		CloudServer: []string{"AWS", "GCP", "DigitalOcean", "Heroku"},
		Architecture: ArchitectureInfo{
			Patterns:   []string{"Microservices", "Event-driven", "System Design"},
			Components: []string{"Docker", "Kubernetes", "Kafka", "GraphQL"},
			Challenges: []string{"Scalability", "Resilience", "Security"},
			Serverless: []string{"Lambda", "API Gateway"},
		},
		Challenge: []string{"Keep getting better, even if it's just 0.001% each day.",
					"Consistency turns those tiny gains into something big"},
		AISkills:  []string{"MachineLearning", "DeepLearning", "AI", "GenAI", "LLM", "ComputerVision"},
	}

	val := reflect.ValueOf(PVHUWUNG)
	for i := 0; i < val.NumField(); i++ {
		field := val.Field(i)
		fieldName := val.Type().Field(i).Name
		fmt.Printf("- %s: %v\n", fieldName, field.Interface())
	}
}
	// Feel free to folk or use, but don't forget to give a star ⭐⭐⭐. Thanks!!!!

activity graph

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Pham Viet Hung *David's Projects

airst-research-paper-summarization icon airst-research-paper-summarization

This AI tool app built on Streamlit library provides a powerful and user-friendly tool through web interface for accessing key information from healthcare-related academic literature. Its natural language processing capabilities and intuitive user interface make it an essential AI tool for anyone working in the healthcare industry.

amplify-hosting icon amplify-hosting

AWS Amplify Hosting provides a Git-based workflow for deploying and hosting fullstack serverless web applications.

api-redoc icon api-redoc

πŸ“˜ OpenAPI/Swagger-generated API Reference Documentation

awesome-go icon awesome-go

A curated list of awesome Go frameworks, libraries and software

cinema-recommendation-systems icon cinema-recommendation-systems

This Python code uses the Pygame and Pygame_menu libraries to create several menus for different cinemas. Built a Sorting algorithm using Pattern Recognition, Decomposition to recommend by locations, prices, vacancies

dlw-queue-monitor icon dlw-queue-monitor

A real-time people counting system for queue management at supermarkets, malls and public areas.

emotion_classifier_app icon emotion_classifier_app

This project is a machine learning application that uses natural language processing techniques to analyze text data and predict the emotions expressed within the text. The application is built using Python and several machine learning libraries, deploy through StreamLit

histopathologic-cancer-detection icon histopathologic-cancer-detection

This repository contains code for a deep learning model that detects cancerous cells in histopathologic images using computer vision. The model utilizes ViT (Vision Transformer) and CovNExt (Convolutional Neural Network with Extra-Width and Random-Erasing Augmentation) architectures for training.

multi_page_streamlit icon multi_page_streamlit

This project is a multipage Streamlit application that allows users to explore and visualize data from a variety of sources. The application is organized into several pages, each with its own set of features and data visualizations. The main pages include:

nextjs-ts-portforlio icon nextjs-ts-portforlio

My portfolio website built with Next.js and TypeScript features a clean design showcasing my skills, projects, and experience. It's fully responsive and available on GitHub for easy customization. I also use Material UI and framer motion for cleaner design

puter icon puter

🌐 The Internet OS! Free, Open-Source, and Self-Hostable.

pvhuwung icon pvhuwung

README Profile anime inspired (Fate/stay night)

reinforcement-learning icon reinforcement-learning

Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning

simplechatbot icon simplechatbot

This is a simple chatbot using Javascript. This is a basic JavaScript program designed to help to learn about the language's syntax and how to use variables, conditions, loops, and functions to create simple programs, such as a chatbot.

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