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

Name: Parallel AI Programming in Python: Build Supercharged ML Workflows That Perform in Production
Brand: Independently Published
SKU: 9798270308827
Price: 1876.0 INR
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ISBN13: 9798270308827
Binding: Paperback
Subject: N/A
Publisher: Independently Published
Publisher Imprint: Independently Published
Publication Date: October 17, 2025
Pages: 194
Original Price: GBP 16.49
Language: English
Edition: N/A
Item Weight: 345 grams
BISAC Subject(s): Distributed Systems / Cloud Computing

About The Book

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

Are you wrestling with slow model training, stalled data pipelines, or unpredictable inference performance? You're not alone-and you don't have to accept sluggish results as the norm.

Parallel AI Programming in Python offers the definitive, hands-on guide to turbocharging your machine learning workflows. From multicore CPU tricks to multi-GPU strategies and distributed architectures, this book equips you with the proven, production-ready techniques that top AI teams use every day.

Inside, you'll discover how to

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

When you put this book into practice, you will

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

Whether you're an ML engineer, data scientist, or infrastructure developer, Parallel AI Programming in Python delivers hands-on labs, clear code examples, and concise checklists to transform sluggish prototypes into production-grade systems.

Take control of your AI pipeline performance today-add this essential resource to your toolkit and watch your Python workflows surge to new speeds.

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