18.6K
UBAI is rapidly evolving, impacting every sector from entertainment to space tech.🌟
Canonical is your ally for open source AI and MLOps tools. Explore our solutions for Kubeflow, MLflow, Spark and more.
#AI #MLOps #Canonical
@ubuntu_os
#Mlops Tools
Guarda 850+ video Reel su Mlops Tools da persone di tutto il mondo.
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850+ posts
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Reel di Tendenza
(12)
26.9K
CO✅ MLOps & LLMOps Tools Ecosystem !
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Don’t forget to save this post for later and follow @codewithbrij for more such information.
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Hashtags (ignore)
#computerscience
#programmers #html5
#css3 #javascriptdeveloper
#webdevelopers #webdev
#ccna #datastructure
#softwaredevelopment
#linux #python3
#pythondeveloper #fullstackdeveloper #datascience #machinelearningalgorithms #fullstackdev #javadeveloper #sql #docker
@codewithbrij
1.9K
JU✅ MLOps & LLMOps Tools Ecosystem !
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Don’t forget to save this post for later and follow @julianvelez1997 for more such information.
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Hashtags (ignore)
Pb @codewithbrij
#computerscience
#programmers #html5
#css3 #javascriptdeveloper
#webdevelopers #webdev
#ccna #datastructure
#softwaredevelopment
#linux #python3
#pythondeveloper #fullstackdeveloper #datascience #machinelearningalgorithms #fullstackdev #javadeveloper #sql #docker
@julianvelez1997
179.7K
JAHere is the MLOps roadmap:
(with resources and courses included)
📌 𝗡𝗼𝘁𝗲:
Red asterisks = Must-have skills
Others = familiarity is enough (especially early on)
▶️ 𝗠𝗟 & 𝗠𝗟𝗢𝗽𝘀 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻*
→ Machine Learning Specialization –
🔗 comment “mlops” for link
→ Designing Machine Learning Systems (Book)
🔗 comment “mlops” for link
→ Model deployment in production
🔗 comment “mlops” for link
▶️ 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 (𝗣𝘆𝘁𝗵𝗼𝗻)*
→ Python general → comment “mlops” for link
→ FastAPI / Flask → comment “mlops” for link
→ Git (Version Control) → comment “mlops” for link
→ Unit Testing → comment “mlops” for link
→ Integration Testing → comment “mlops” for link
→ Docker (Must) → comment “mlops” for link
→ CI/CD (only one) → comment “mlops” for link
🔗 GitHub Actions → comment “mlops” for link
🔗 CircleCI → comment “mlops” for link
🔗 Jenkins → comment “mlops” for link
→ Load Testing (Locust) - comment “mlops” for link
→ A/B Testing - 🔗 comment “mlops” for link
▶️ 𝗖𝗹𝗼𝘂𝗱 𝗜𝗻𝗳𝗿𝗮 (𝗜𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁)*
Pick one cloud provider. Learn via certification paths.
→ AWS SageMaker (overview) - comment “mlops” for link
→ AWS Learning Path:
1️⃣ AWS Cloud Practitioner (free) → comment “mlops” for link
2️⃣ AWS ML Associate → comment “mlops” for link
3️⃣ AWS ML Specialty → comment “mlops” for link
(Also: GCP Vertex AI, Azure ML)
▶️ 𝗘𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁 𝗧𝗿𝗮𝗰𝗸𝗶𝗻𝗴 & 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴
→ MLflow* - 🔗 comment “mlops” for link
→ Grafana + Prometheus - 🔗 comment “mlops” for link
→ DataDog - 🔗 comment “mlops” for link
▶️ 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 & 𝗦𝗲𝗿𝘃𝗶𝗻𝗴
→ Apache Airflow (good to know) - 🔗 comment “mlops” for link
→ Kubeflow (best with GCP)
→ MetaFlow
→ EC2 / ECS / Kubernetes / Step Functions
(Skip Kubernetes early on if possible)
🚨𝗥𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗲𝗱 𝗖𝗼𝘂𝗿𝘀𝗲𝘀
→ MLOps Zoomcamp (DataTalksClub)
🔗 comment “mlops” for link
→ MadeWithML by Goku
🔗 comment “mlops” for link
→ Train & Deploy ML (GitHub)
🔗 comment “mlops” for link
→ Taking Python to Production
🔗 comment “mlops” for link
#machinelearning #mlops #datascience #ai #coding
@jam.with.ai
905.5K
COMachine learning projects are changing! Save this post for later! 📖
Gone are the days when ML was just about tweaking your logistic regression in a Jupyter Notebook.
Today, it's about building end-to-end solutions, integrating systems, ensuring scalability, and maintaining robustness in production environments.
If you're a software engineer, it's not just about knowing Python or TensorFlow; it's about applying core engineering principles—modular design, version control, testing, and CI/CD pipelines—into AI development.
📌So, how do you get started?
Learn the basics of ML, but don’t stop there.
Master frameworks like TensorFlow, PyTorch, and MLOps tools.
Focus on deployment, monitoring, and optimization at scale.
The future belongs to those who merge software craftsmanship with AI.
Start now, because the lines between ML and software engineering are disappearing fast, and it’ll no longer be the skill reserved for the data people only but also software developers.
I can help you break the barrier, because I created a detailed, instruction-based machine learning engineer path, ideal for beginners, as well as professional software developers, data scientists and data engineers, as well as DevOps engineers who want to make a career swap to MLOps
I’ll be sending it to you only for the next 24h so
Follow @codingmermaid.ai
Comment “september” to this reel for invitation!
Much love,
Danica 🤍
#datascience #deeplearning #machinelearning #mlops #devops #software #developers #coding #python #webdeveloper #machinelearningtools #Machinelearningmodel #machinelearningalgorithms #deeplearningmodel #machinelearningproject #decisiontrees #neuralnetworks #naturallanguageprocessing
@codingmermaid.ai
52.1K
PAGPU chahiye ya sirf jugaad?
Infra chahiye ya imported solution?
Build karo ya borrow?
Jab AI banane ka craze hai,
toh India ka apna AI base bhi zaroori hai!
Aur Neysa wahi laa raha hai —
GPU cloud, MLOps tools, training platform — sab kuch ek jagah!
Ab ChatGPT banane ka sapna sirf Silicon Valley tak limited nahi hai 🔥
Neysa is India’s answer to the AI infra gap.
Backed by $50M, trusted by 200+ startups, and now going global.
👇Aap batao — agar infra mil jaaye, toh kya aap bhi AI product banayenge?
[AIRevolution, MadeInIndia, TechStartup, GPUCloud, MLOpsIndia, FutureOfAI, NeysaInfra]
#PaajiPlease #TechKaTandoor #StartupIndia #DigitalBharat #AIIndia #InfraMatters #GenAI
@paajiplease
77.3K
PR1. Programming Basics
- Learn Python (your main tool for ML + MLOps)
- Write clean and reusable code (functions, modules, simple classes)
- Get comfortable with testing your code (use pytest or unittest)
2. Data Handling
- Learn how to work with CSV, JSON, and databases
- Practice ETL basics → load, clean, and transform data
- Use SQL to query data
3. Machine Learning Foundations
- Understand basic ML concepts (train, test, validate models)
- Use libraries like scikit-learn, TensorFlow, or PyTorch
- Track experiments with MLflow (beginner-friendly)
4. DevOps & Cloud (Intro Level)
- Learn Git & GitHub (version control)
- Try Docker (package your code in a container)
- Use a free cloud tier (AWS/GCP/Azure) to run ML models
5. MLOps Tools
- MLflow → track models
- DVC → version datasets and models
- FastAPI or Flask → deploy a simple ML model as an API
6. Monitoring (Simple Start)
- Log model predictions and errors
- Track accuracy over time
- Basic dashboards with Grafana or even Excel at first
7. Security & Best Practices
- Store credentials safely (not in your code!)
- Learn basics of data privacy (don’t expose sensitive info)
8. Soft Skills
- Work with teams using GitHub projects/boards
- Document your code and steps clearly
- Ask good questions, be open to feedback
#datascience #machinelearning #womeninstem #learningtogether #progresseveryday #tech #consistency
@priyal.py
22.2K
CLLearn MLOps & Other Tools From CloudyML Website. Check out now.
Become Job-Ready @ Most Affordable Price. Link in my bio
#datascience #datasciencejobs #dataanalytics #mlops #computerscience #machinelearning #deeplearning #artificialintelligence #chatgpt #algorithms #bigdata #python #sql #fresher #job #career #programmer #programming #fullstackdeveloper
@cloudyml.akash
11.7K
BAIf I were starting today, I’d focus on:
• Data Visualization
• MLOps
• Vector Databases
• AutoML Tools
• Agentic Workflows
I made a free guide with my favorite resources for each.
Comment SWE and I’ll dm it to you rn
@bashi_fuirkashi
313.6K
UDAI Agents Banana Aata Hai??🤯🔥
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{ai engineering, iit roorkee, huggingface, langchain, mlops, ai tools, ai agents, tech career, coding, ai future}
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#reel #coding #tech #artificialintelligence #iitroorkee #langchain #huggingface #mlops #ai #machinelearning
@udaysharmaaaaa
![#Mlops Tools Reel by @kodekloud (verified account) - Dive into our 'Fundamentals of MLOps' course and master the art of deploying and managing ML models like a pro! ⬇️
ENROLL HERE: [LINK IN BIO]
By the](https://image.pictame.com/img/503232200_691373537017986_1878933206637503392_n.jpg?hash=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)
5.7K
KODive into our 'Fundamentals of MLOps' course and master the art of deploying and managing ML models like a pro! ⬇️
ENROLL HERE: [LINK IN BIO]
By the end, you'll have the skills to design, deploy, monitor, and manage ML models while integrating DevOps expertise with the latest machine learning techniques.
@kodekloud
1.9K
TESave it for future and follow for more
Credit - respective owner
#corporate #9to5 #softwaredeveloper
@techyguywithhacks
✨ Guida alla Scoperta #Mlops Tools
Instagram ospita 850+ post sotto #Mlops Tools, creando uno degli ecosistemi visivi più vivaci della piattaforma.
#Mlops Tools è uno dei trend più coinvolgenti su Instagram in questo momento. Con oltre 850+ post in questa categoria, creator come @codingmermaid.ai, @udaysharmaaaaa and @jam.with.ai stanno guidando la strada con i loro contenuti virali. Esplora questi video popolari in modo anonimo su Pictame.
Cosa è di tendenza in #Mlops Tools? I video Reels più visti e i contenuti virali sono in evidenza sopra.
Categorie Popolari
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🌟 Creator in Evidenza: @codingmermaid.ai, @udaysharmaaaaa, @jam.with.ai e altri guidano la community
Domande Frequenti Su #Mlops Tools
Con Pictame, puoi sfogliare tutti i reels e i video #Mlops Tools senza accedere a Instagram. La tua attività rimane completamente privata - nessuna traccia, nessun account richiesto. Basta cercare l'hashtag e inizia a esplorare il contenuto di tendenza istantaneamente.
Analisi delle Performance
Analisi di 12 reel
💡 I post top ottengono in media 369.0K visualizzazioni (2.7x sopra media)
Posta regolarmente 3-5x/settimana in orari attivi
Suggerimenti per la Creazione di Contenuti e Strategia
💡 I contenuti top ottengono oltre 10K visualizzazioni - concentrati sui primi 3 secondi
📹 I video verticali di alta qualità (9:16) funzionano meglio per #Mlops Tools - usa una buona illuminazione e audio chiaro
✨ Molti creator verificati sono attivi (50%) - studia il loro stile di contenuto
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Mlops Tools ReelsGuardare Mlops Tools Video
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Esplorare Mlops Tools#tools#tool#tooling#tooled#tooles#mlop#toolings#toole