Key words: JupyterNotebook, Anaconda, AWS, EC2, Proxy, Winscp, Putty, DeepLearning <Background> The company employs a proxy server, through which all external connections must pass. Company computers utilize Virtual Desktop Infrastructure (VDI), restricting the installation of large software such as Anaconda. <Task> As a Deep Learning engineer, it is necessary to set up a Jupyter Notebook environment on AWS cloud. However, services like SageMaker are costly, thus requiring a self-built environment on AWS EC2. <AWS EC2 Configuration> Create an EC2 Instance with the following specifications: AMI: Ubuntu/Amazon Linux 2 AMI CPU: t3.large VPC: Public subnet with an Internet Gateway (IGW) Elastic IP: Required, as dynamic IP addresses are prone to firewall interception. Security Group: Inbound ports 8081 (Jupyter) and 22 (SSH) should be open; all outbound ports should be accessible. Storage: Minimum of 16GB, as Anaconda alone requires 9GB. Key Pair: Generate an RSA key pair,...
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