Artículo: AMZ-B0FWPQVT1B

Parallel AI Programming in Python: Build Supercharged ML Workflows That Perform in Production

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0.20 kg
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Producto de
Amazon

Sobre este producto
  • Leverage Python’s threading and multiprocessing to blast past the Global Interpreter Lock
  • Build high-throughput I/O pipelines with asyncio, Dask, and Ray for lightning-fast data ingestion
  • Master GPU parallelism with PyTorch DDP, NCCL tuning, and mixed-precision training
  • Scale across clusters using MPI, Ray, and Dask—and know exactly when adding nodes stops delivering gains
  • Optimize numeric kernels with NumPy, Numba, Cython, and native extensions for peak performance
  • Implement real-time, fault-tolerant pipelines with Kafka/Pulsar, backpressure, and exactly-once semantics
  • Profile, benchmark, and tune your code with cProfile, py-spy, perf, and NVIDIA Nsight to fix bottlenecks fast
  • Cut training times from days to hours using multi-GPU and distributed training patterns
  • Architect data pipelines that process millions of records per second without dropping a message
  • Deploy inference services that scale horizontally and maintain sub-100ms latency under heavy load
  • Detect and remedy performance pitfalls—from memory thrashing to straggler tasks—before they hit production
  • Maintain rock-solid environments with containerized setups, dependency pinning, and reproducible scripts

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