Docker or Podman, whichever fits for your use case

Let me clarify few terms here. Docker and Containers are related but distinct technologies. A Container is the core technology that packages your application code along with the necessary dependencies into a single unit. It requires a runtime to operate on a virtual machine or server. Docker is a tool that provides this runtime to… Continue reading Docker or Podman, whichever fits for your use case

Hardware role for ML

Continuation from here https://joyantablog.wordpress.com/2025/04/08/neural-network-dive-deeper/ Let’s continue exploring the hardware magic behind long machine learning tasks like training and inference. In my previous post, I discussed how tools like TensorFlow and PyTorch offload resource management and expose optimal approaches through libraries and APIs. This enables you to focus on understanding the methods and functionalities, applying them… Continue reading Hardware role for ML

Neural network, Dive Deeper

Continuation from here . What discussed so far how micro services helps implementing server-less architecture for Neural network based architecture. In this article I will talk few interesting topics like parallel computing, how ML library tools helps implementing smart resource management, and finish by giving a touch hardware solutions from NVIDIA helps accelerating ML progress.… Continue reading Neural network, Dive Deeper

MicroService concept, philosophy and ML importance

Continuation from here. In that article, I explored how a microservice-based solution can address several limitations of serverless computing. For instance, AWS Lambda’s time limit for running long tasks can be mitigated by moving to containerized solutions. In this article, I’ll dive deeper into the microservice concept and explain why it’s crucial for enabling true… Continue reading MicroService concept, philosophy and ML importance