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Building and deploying ML prototypes is faster than ever. We've moved from a model-centric approach to data-centric, and now to a task-driven one, where pre-trained models make it easier to adapt AI to new tasks, often without needing any training data. In this article, I share how techniques like fine-tuning, prompting, zero-shot, and AutoML can help you quickly solve ML problems. Take a look if you're interested in speeding up your ML development! #ml #ai #machinelearning #artificialintelligence #prototyping #automl #deeplearning #datascience #tech