Youtor
Docker Simply Explained with a Machine Learning Project for Beginners
>> YOUR LINK HERE: ___ http://youtube.com/watch?v=-l7YocEQtA0
Today we will finally learn how to work with Docker! 🐋🐋🐋 • We will focus on understanding the concept of containers, images and Dockerfiles in simple terms with lots of helpful visualizations and hands-on examples! We will focus on the logic behind each Docker component, not only in terms of how it works - but also what problems does it solve and what happens if we do not use it! 🤓 • Codewise, will see a step by step workflow of developing an incredibly simple Machine Learning program using the Huggingface Transformers library. We will build our own custom Docker image based on the Jupyter Tensorflow Notebook one. And we will even learn how to deploy our finished project to DokcerHub! 🚀🚀🚀 • By the end of this video - you will have your very own video captions translating software as well as a comprehensive understanding of Docker (regardless of your level of experience with programming). • 🤖 ML and AI Development with Docker 🤖 • --------------------------------------------------------------------- • https://www.docker.com/products/ai-ml... • 🐋 Pull Tutorial Image 🐋 • --------------------------------------------------------------------- • https://hub.docker.com/repository/doc... • 🎥 Related Videos of Mine 🎥 • --------------------------------------------------------------------- • ⭐ MNIST Tutorial - Machine Learning Databases: • • Machine Learning Databases and How to... • ⭐ Python For Loops: • • Python For Loops - Programming for Be... • ⏰ TIMESTAMPS ⏰ • --------------------------------------------------------------------- • 00:00 - 00:40 | Intro • 00:40 - 02:21 | What is Docker? What are containers? • 02:21 - 03:06 | Install Docker • 03:06 - 04:17 | What are Docker Images? • 04:14 - 05:20 | Search and Pull Images • 05:20 - 06:08 | Run Container • 06:08 - 07:18 | Expose Container Port • 07:18 - 08:10 | Load MNIST Dataset with Tensorflow • 08:10 - 09:47 | Plot MNIST sample • 09:47 - 11:11 | Run Containers with Docker Compose • 11:11 - 12:02 | Replace Jupyter Token with Password • 12:02 - 13:07 | Mount Drive • 13:07 - 13:32 | Build Images with Docker Compose • 13:32 - 15:29 | Dockerfile • 15:29 - 17:06 | Translate Text with Transformers • 17:06 - 19:26 | copy files from system to image • 20:52 - 21:14 | create public repository on DockerHub • 21:14 - 23:04 | push local image to remote repository • 23:04 - 25:11 | clean up containers and images • 25:11 - 25:31 | thank you for watching! • 💻 Download my SRT Demo Subtitles File 💻 • ---------------------------------------------------------------- • https://drive.google.com/file/d/16bCS... • (new link coming soon... or you can pull it directly from Docker Hub with docker pull mariyasha/srt-translator ) • 🤝 Connect with me 🤝 • ---------------------------------------------------------------- • 🔗 Github: • https://github.com/mariyasha • 🔗 Discord: • / discord • 🔗 LinkedIn: • / mariyasha888 • 🔗 Twitter: • / mariyasha888 • 🔗 Blog: • https://www.pythonsimplified.org • 💳 Credits 💳 • ---------------------------------------------------------------- • ⭐ Beautiful titles, transitions, sound FX: • mixkit.co • ⭐ Beautiful icons: • flaticon.com • ⭐ Beautiful graphics: • freepik.com • #python #pythonprogramming #machinelearning #artificialintelligence #datascience #tensorflow #programming #coding #application #neuralnetworks #ml #ai #technology #computer #computerscience #transformers #huggingface #docker #dockertraining #translation #captions #container #datascience #dockerhub
#############################
