21.1K
ITDeploy your website for free in 30 seconds
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#code #coding #ai #website #deploy deployment #trending #viral #pyp #foryou #chatgpt
@its_aman_codes
#Dpl Deploy Tool Gitlab
Смотрите Reels видео о Dpl Deploy Tool Gitlab от людей со всего мира.
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Трендовые Reels
(12)
6.5K
MOCI/CD Pipelines automate build → test → deploy, so every code change is shipped faster, safer, and repeatedly without manual steps.
Jenkins
Self-hosted, highly customizable CI/CD tool with thousands of plugins — great when you need full control over pipelines and infrastructure.
GitHub Actions
Native to GitHub, YAML-based workflows triggered directly from repos — simple setup, tight GitHub integration, and less maintenance.
Other popular CI/CD tools: GitLab CI, CircleCI, Azure DevOps
#distributedsystems #systemdesign #code #tech #programming
@morethancodebase
206.1K
MALet’s deploy a project together with GPU resources because your girl does not own a GPU!
Comment what is the hardest part for you about deployment - is it just getting started? Learning the basics? Optimizing costs? Hopefully we can do some more videos and make learning be simplified and fun 🤩 #cloudcomputing #gpu #nvidia #huggingface
@mar_antaya
998
CODeploy Your AI Agent App for FREE in Minutes Using Streamlite!
You've built an AI agent locally, but how do you share it with your team or get user feedback? The answer is Streamlit Cloud.
This video shows you how to deploy your AI project to a live, public URL for free. It's the perfect solution for:
✅ Creating a quick Proof of Concept (POC).
✅ Getting fast feedback from users.
✅ Sharing your work without complex DevOps.
Whole video link: https://www.youtube.com/watch?v=y7damsm8Qos&t=474s
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#Streamlit #AIdemo #Deployment #MLOps #GitHub #Developer #POC #AIapp #google #cloud #genai #ai #agent #artificial #intelligence #coding
@code.with.ahsan
15.4K
U_How to Deploy Projects Using GitHub
Follow Us @u_day_codes
#github #deploy #deployment #git #githubpages #coding #html #css #js #webdevelopment #btech #udaycodes
@u_day_codes
22.8K
DAJoin Free Telegram Channel (Link in Bio)
Video Credit: Alejandro AO - Software
@dailyaionly
1.1K
DADo you know how companies like Amazon, Netflix, and banks deploy new features without downtime?
In this video, we break down Blue-Green vs Rolling deployment strategies with a simple visual explanation.
You’ll understand how real companies release updates safely, when to use each strategy, and which one is commonly asked in system design interviews.
Perfect for:
System Design interview prep
DevOps & Cloud engineers
Backend & Data Engineers
Follow DataStreak for daily system design and cloud concepts 🚀
#systemdesign
#devops
#cloudcomputing
#kubernetes
#softwareengineering
@datastreakofficial
477
STCLR code ko run karta hai,
BCL ready-made tools deta hai,
aur MSIL code ko machine tak le jaata hai.
Agar aap interview-ready .NET developer banna chahte ho,
to basics strong hona mandatory hai 💯
📌 Comment DOTNET for roadmap & PDFs
👉 Follow for next episode 🚀
dotnet internals
clr bcl msil
dotnet interview preparation
dotnet for freshers
dotnet developer roadmap
how dotnet works
#dotnet
#dotnetdeveloper
#dotnetcore
#clr
#bcl
#msil
#dotnetinterview
#softwaredeveloperlife
#codingcareer
#fullstackdotnet
#developerindia
#techcareers #stackbytes #integerbyte
@stack.bytes
121.4K
MAComment PROJECT to access my step-by-step Python tutorial that anyone can follow to build your very first geospatial dashboard web app! 🌍📊
A good number of portfolio projects is 3–5, and the types of projects you choose should reflect the kind of data role you’re going after.
A data analyst portfolio should look very different from a machine learning engineer one. Even within data science, a product/decision data scientist portfolio should focus on A/B testing and metrics storytelling—while an algorithm data scientist portfolio might highlight modeling and experimentation.
✨ Especially if you’re building your very first project, prioritize:
🌱 Real-world messiness (not polished Kaggle sets)
🌱 Business context and decision-making
🌱 Clear documentation (what you did and why)
🌱Visuals to help your work stand out
No one’s asking for perfection—they want to see how you think.
#datascienceportfolio #dataanalyst #learnpython #codingjourney #techcareers
@maggieindata
185.3K
PR1. LLM Chatbot – Deploy a chatbot using Ollama with a locally running model.
2. Summarization Tool – Create a script that summarizes long articles or PDFs.
3. Code Completion Assistant – Use CodeLlama for local AI-powered code suggestions.
4. Text-to-SQL Generator – Convert natural language queries into SQL using an LLM.
5. RAG Pipeline with Ollama – Implement a retrieval-augmented generation system.
6. AI-Powered Note-Taking App – Summarize and categorize notes in real-time.
7. Personalized Study Assistant – Build an AI tutor based on your course materials.
8. PDF Q&A Bot – Ask questions from research papers using Ollama + LangChain.
9. Local AI Agent for Automation – Use CrewAI + Ollama to automate tasks.
10. Voice Assistant – Convert speech to text and interact with an LLM using Ollama.
#datascience #machinelearning #womeninstem #learningtogether #progresseveryday #tech #consistency
@priyal.py
180.7K
PE9 data projects ideas instead of doomscrolling:
(And there is a repo with the data :) )
🤖 Machine Learning Projects
* Diabetes Classification
Build and compare classification models to show how data preprocessing, feature scaling, and hyperparameter tuning directly improve predictive performance.
* Heart Attack Prediction
Implement an end-to-end classification pipeline—from raw data to model evaluation—to demonstrate a realistic machine learning workflow.
* Medical Cost Prediction
Train a regression model to predict healthcare costs, emphasizing feature importance analysis and model optimization to explain what drives predictions.
🛠️ Data Engineering Projects
* NBA Player Statistics ETL Pipeline
Design an ETL pipeline that extracts player statistics, cleans and transforms the data, and stores it in a relational database for reliable downstream analysis.
* Real-Time & Batch Data Pipelines with Kafka
Build a scalable pipeline that processes streaming and batch data using Kafka, PostgreSQL, and Docker to demonstrate modern data flow architecture.
* Glassdoor Job Data Pipeline
Scrape job postings, clean and structure the raw data, and prepare it for analysis and visualization to showcase real-world data ingestion challenges.
📊 Data Analytics Projects
* Pokémon Dataset Analysis
Perform exploratory data analysis and feature engineering to uncover patterns in Pokémon characteristics such as types, stats, and legendary status.
* Automated EDA Tool Comparison
Benchmark AutoViz, SweetViz, and Pandas Profiling across multiple datasets to evaluate performance, resource usage, and practical trade-offs.
* Exploratory Job Market Analysis
Analyze cleaned job posting data to extract trends, key skills, and role distributions using visualizations and summary statistics.
👉🏻 Comment « data » to get the link to the repo and portfolio strategies!
#data #students #job
@penelope_data
240.6K
FLControl Engineering 101:
PID controller with feedback from IMU makes the system stable with minor errors that can be tuned further.
Comment/DM if you want to join full course on control engineering.
#pid #controlengineering #controller #matlab #python #arduino #robotics #esp32 #engineering #engineers
@flywheelrobotics
✨ Руководство по #Dpl Deploy Tool Gitlab
Instagram содержит thousands of публикаций под #Dpl Deploy Tool Gitlab, создавая одну из самых ярких визуальных экосистем платформы.
#Dpl Deploy Tool Gitlab — один из самых популярных трендов в Instagram прямо сейчас. С более чем thousands of публикаций в этой категории, создатели вроде @flywheelrobotics, @mar_antaya and @priyal.py лидируют со своим вирусным контентом. Просматривайте эти популярные видео анонимно на Pictame.
Что в тренде в #Dpl Deploy Tool Gitlab? Самые просматриваемые видео Reels и вирусный контент представлены выше.
Популярные Категории
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🌟 Избранные Создатели: @flywheelrobotics, @mar_antaya, @priyal.py и другие ведут сообщество
Часто задаваемые вопросы о #Dpl Deploy Tool Gitlab
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Анализ Эффективности
Анализ 12 роликов
💡 Лучшие посты получают в среднем 203.2K просмотров (в 2.4x раз выше среднего)
Фокус на пиковые часы (11-13, 19-21) и трендовые форматы
Советы по Созданию Контента и Стратегия
💡 Лучший контент получает более 10K просмотров - сосредоточьтесь на первых 3 секундах
✍️ Подробные подписи с историей работают хорошо - средняя длина 595 символов
✨ Многие верифицированные создатели активны (42%) - изучайте их стиль контента
📹 Вертикальные видео высокого качества (9:16) лучше всего работают для #Dpl Deploy Tool Gitlab - используйте хорошее освещение и четкий звук
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Исследовать Dpl Deploy Tool Gitlab#tools#dpl#tool#deployment#toole#deployed#deploy#gitlab