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    AI/ML development & inference using Python & Jupyter by Techlatest.net

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    AWS Free Tier
    This product has charges associated with it for seller support. This VM offers a hassle-free setup with <b>Jupyter</b> for projects, <b>Jupyterhub</b> for multiuser collaboration, a <b>Jupyter AI extension</b> for for <b>LLM and Generative AI development</b>, and preloaded popular libraries like TensorFlow and PyTorch. It also comes with pre-configured <b>NVIDIA GPU drivers and CUDA libraries</b>.
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    AI/ML development & inference using Python & Jupyter by Techlatest.net

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    Overview

    This is a repackaged open source software product wherein additional charges apply for support by TechLatest.net.

    Important: For step by step guide on how to setup this vm , please refer to our Getting Started guide 

    If you are AI/ML practitioner or someone who is starting their AI/ML journey but do not want to spend hours setting up the right environment , this VM is for you. It includes :

    1. Jupyter : Your AI/ML Playground
    2. Jupyterhub: Making your AI/ML projects more collaborative by providing multi-user environment and enabling easy code and data sharing 3. Jupyter AI extension  : your gateway to generative AI within Jupyter
    3. Provides better data privacy and control as your data, models, code & other information is stored on the VM
    4. Preinstalled popular AI/ML libraries such as TensorFlow, PyTorch, scikit-learn and many more
    5. Pre-configured NVIDIA GPU drivers & CUDA libraries

    The preinstalled Juputer and AI/ML libraries jump-start your AI/ML development by saving you hours of installation time.


    Jupyterhub gives you the collaboration capabilities by allowing a multi-user environment within the same VM. This not only makes it easy to share the AI/ML work , but makes it more cost efficient in a team setup by allowing multiple users/team members to share the same VM infrastructure instead of each user creating their own VM/notebooks.


    With the Jupyter AI  extension, you can seamlessly integrate with 100+ widely used LLMs from 10+ model providers such as OpenAI for ChatGPT, Anthropic, Hugging Face, AI21, SageMaker to name a few. Complete list of supported LLM Model providers is available here .


    The JupyterAI extension comes with built-in LLM Chat UI for seamless collaboration for generative AI. Enjoy flexibility with support for diverse models and providers, seek code suggestions, debugging tips, or even have code snippets generated for you by interacting with the chat UI.


    In addition to the Chat UI, the JupyterAI extension comes with %ai and %%ai magic commands turning your Jupyter into a generative AI playground anywhere the IPython kernel runs!


    The VM also has pre-configured NVIDIA GPU drivers & CUDA libraries saving you hours of driver setup and configuration hassle so you can harness the power of GPU resources for your AI/ML workload and conduct advanced data analysis with ease.


    Highlights

    • Multi User Jupyter notebook with AI/ML setup for LLM & Generative-AI
    • Unleash the Power of Python, Jupyter & GPU: Accelerate Your Machine Learning Journey on the Cloud
    • AI & ML Collaboration & Innovation : Unleash the Power of Multi-User Jupyter with GPU for AI & ML development, training & inference

    Details

    Delivery method

    Delivery option
    64-bit (x86) Amazon Machine Image (AMI)

    Latest version

    Operating system
    Ubuntu 22.0.4

    Typical total price

    This estimate is based on use of the seller's recommended configuration (t2.large) in the US East (N. Virginia) Region. View pricing details

    $0.243/hour

    Pricing

    AI/ML development & inference using Python & Jupyter by Techlatest.net

     Info
    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Usage costs (208)

     Info
    • ...
    Instance type
    Product cost/hour
    EC2 cost/hour
    Total/hour
    t2.nano
    $0.15
    $0.006
    $0.156
    t2.micro
    AWS Free Tier
    $0.15
    $0.012
    $0.162
    t2.small
    $0.15
    $0.023
    $0.173
    t2.medium
    $0.15
    $0.046
    $0.196
    t2.large
    Recommended
    $0.15
    $0.093
    $0.243
    t2.xlarge
    $0.15
    $0.186
    $0.336
    t2.2xlarge
    $0.15
    $0.371
    $0.521
    t3.nano
    $0.15
    $0.005
    $0.155
    t3.micro
    AWS Free Tier
    $0.15
    $0.01
    $0.16
    t3.small
    $0.15
    $0.021
    $0.171

    Additional AWS infrastructure costs

    Type
    Cost
    EBS General Purpose SSD (gp2) volumes
    $0.10/per GB/month of provisioned storage

    Vendor refund policy

    Will be charged for usage, can be canceled anytime and usage fee is non refundable.

    Legal

    Vendor terms and conditions

    Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .

    Content disclaimer

    Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.

    Usage information

     Info

    Delivery details

    64-bit (x86) Amazon Machine Image (AMI)

    Amazon Machine Image (AMI)

    An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.

    Version release notes

    Machine Learning Kit on Ubuntu 22.04 with latest Jupyter AI Notebook with support of NVIDIA GPU.

    Additional details

    Usage instructions

    Getting started guide:

    1. Login to instance using SSH via key based authentication. Use "ubuntu" as userid (refer https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/putty.html  for details on how to connect using putty/ssh)
    2. Once connected using ssh/putty, run below command to set the password for "ubuntu" user on the terminal sudo passwd ubuntu
    3. Once the password is set for ubuntu user, from your local windows machine, goto start menu.
    4. On the start menu, search & select "remote desktop connection" .
    5. In the "remote desktop connection" wizard, provide public IP of your instance & click connect.
    6. In the displayed window, provide "ubuntu" as userid & password set in step 2 above.
    7. Now you are connected to the desktop environment of the VM where you can access out of box environment for python AI & machine learning .
    8. You can use the remote desktop you connected in above step for using the VM, however, more convenient & better method is to use the Jupyter,Ipython notebook which comes with the VM . The Notebook is available on the same public IP you used for remote desktop & accessible via any browser. Just open the browser & type the public IP address http://yourpublicip  & you will get screen for login . Use "ubuntu" as username & the password you set in step 2 to login. Make sure you use http & not https in the url visit http://www.techlatest.net/support/python_ai_machine_learning_support/aws_gettingstartedguide  for more details

    Resources

    Vendor resources

    Support

    Vendor support

    AWS infrastructure support

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

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