1. What Is MLOps MLOps is short for Machine Learning Operations, and it describes the standardization and engineering of the entire lifecycle around model development. MLOps includes the following key steps: Data management: storing, accessing, cleaning, and transforming data Model development: algorithm development and model construction Model training and tuning: training models on data, adjusting hyperparameters to optimize the model, and fine-tuning models Model evaluation: testing a model’s accuracy, generalization ability, and performance metrics Model deployment: deploying the model to the target environment and converting the model Model monitoring: monitoring the model’s behavior, performance degradation, data drift, and robustness Another similar concept is ModelOps.

1. Data Parallelism Training steps: The master device loads the model and copies the model parameters to every worker device The master device splits the training data along the batch dimension and passes each batch to every worker device Each worker device performs training The master device aggregates the gradients from each worker device and updates the model parameters The master device broadcasts the model parameters to every worker device, preparing for the next batch of training Core idea:

1. What the Image Tag Suffixes Mean base/cuda: includes the CUDA runtime runtime: builds on base, adding the CUDA math libraries and the NCCL and cuDNN runtimes devel: builds on runtime, adding headers and the development tools used to build CUDA images; particularly useful for multi-stage builds cuddn: builds on the above, adding the cuDNN neural network acceleration library

1. Installing conda 1 2 3 wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh bash Miniconda3-latest-Linux-x86_64.sh rm -rf Miniconda3-latest-Linux-x86_64.sh However, Miniconda cannot be used for free at large-scale commercial deployments, so you can use Miniforge as a drop-in alternative. 1 2 wget "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh" bash Miniforge3-$(uname)-$(uname -m).sh 2. Changing the default configuration 2.1 Initializing the Shell Without initialization, activating an environment reports CondaError: Run 'conda init' before 'conda activate'.

1. How Argo Events Works The diagram above is from the official Argo Events website. An event processing system has three important parts: Ingesting event sources, which corresponds to the Event Source Distributing events, which corresponds to the Event Sensor Consuming events, which corresponds to the Event Trigger The event messages are stored in the EventBus, which uses NATS by default.