TensorFlow: the ML elephant that's still standing

Short summary

TensorFlow remains essential in production ML workflows, especially for mobile and edge deployment. TFLite excels where PyTorch lacks maturity; paired with TensorFlow Serving, it handles billions of requests. Best for teams managing complex deployment pipelines; overkill for research or simple services.

• •TensorFlow's strength is deployment maturity, not training elegance—TFLite has no PyTorch equivalent for mobile
• •Real-world production matters: migration feasibility, serving latency, and ecosystem integration outweigh research trends
• •Use TensorFlow for complex infrastructure; use PyTorch for research; use simpler tools for basic services

Generated with AI, which can make mistakes.