From the course: Defending and Deploying AI by Pearson
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Choosing the operating system: Linux, Windows, and macOS
From the course: Defending and Deploying AI by Pearson
Choosing the operating system: Linux, Windows, and macOS
Now we're going into another decision that you have to make, which is choosing the right operating system for your AI development environment. So let's start with the most popular choice among the AI community, which is Linux. I personally use Linux at home in this system that you see in here and many others, including many clusters running Proxmox and other environments for building labs, for ethical hacking, for instant response, and so on, since I am mostly concentrated in cybersecurity. However, for my AI lab, definitely my choice is Linux. First, it's open source. It's definitely customizable. There are tons and tons of libraries for Linux that are related to machine learning and AI nowadays. And it allows you to optimize your system for specific workloads. The other thing is most AI frameworks and tools are developed within Linux in mind. And this makes it the first platform to receive updates and new features in many cases. For the Linux distribution, I am just running Debian…
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Learning objectives1m 27s
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Overview of AI labs and sandboxes: Home-based vs. cloud-based7m 4s
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Choosing the right hardware: GPUs, CPUs, and memory10m 9s
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Building or buying prebuilt systems3m 53s
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Choosing the operating system: Linux, Windows, and macOS4m 21s
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Surveying essential software: Python, Anaconda, Jupyter Notebooks, and other frameworks4m 41s
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Introducing Hugging Face3m 42s
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Introducing Ollama3m 38s
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Installing Ollama6m 24s
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Ollama integrations14m 42s
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Exploring the Ollama REST API3m 3s
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Exploring RAG5m 24s
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Leveraging RAGFlow13m 56s
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