Books

What matters is your direction, not your speed. Roberto Canales Mora brings fifteen years of teaching executives into a practical journey through 75 laws, cases, and exercises for people who lead teams and those preparing to do so.

What becomes possible when different forms of knowing remain distinct, yet still become consequential to one another? Integral — Epistemic Integration explores representation, interface, correspondence, and further relation without forcing premature unity. This is a disciplined inquiry into how integration may be approached without collapse.

Lo importante es la dirección, no la velocidad. Roberto Canales Mora reúne quince años de clases a directivos en un recorrido para crecer profesionalmente, construir equipos y vivir mejor. 75 leyes, casos y ejercicios para quienes ya lideran y quienes se preparan para hacerlo, en PDF y audiolibro.

Can you trace every tonne of CO₂e from the furnace to the finished steel product—and defend the result? Learn ISO 14067 through worked calculations, three steelmaking routes, and a complete industrial case study.

قبل أن تبدأ تجارتك وتضع أموالك في مشروعك، تعلّم كيف تختبر الفكرة، وتفهم السوق والعميل، وتكتشف المخاطر قبل أن تتحول إلى خسائر. ابدأ بالمعرفة قبل أن تبدأ بالمال.

Build the practical skills to run better stores, serve customers, control inventory, improve profitability, and lead retail teams with confidence.

The ultimate technical blueprint for developers and AI engineers to strip away execution overhead, leverage hardware-accelerated NumPy/PyTorch operations, and scale Python code effortlessly

المنظومة الكاملة لاحتراف الاسكالبينج على الناسداك في كتاب يتجاوز 675 صفحة، يأخذك من فهم السوق والسيولة وحركة السعر إلى دراسة الاستراتيجيات وبناء منظومة التداول وتجهيز بيئة العمل والتخطيط والتنفيذ والتطبيق العملي. منهج متكامل يساعدك على تنظيم عملية دراسة السوق والتعامل مع جلسات التداول وفق قواعد واضحة.

From learner to advanced consulting practitioner — a practical programme for designing, calculating, reporting and reviewing defensible GHG inventories under ISO 14064-1, with industrial case studies, worked calculations and professional consulting tools.

About the Book Running an LLM is one problem. Understanding its memory footprint, execution phases, and serving behavior is another.LLM Inference Engine Architecture explores the engineering behind language-model inference—from prefill and decode to KV-cache management, attention kernels, quantization, and request scheduling.Written for software engineers and ML engineers with a working knowledge of Python and transformer fundamentals, the book connects mathematical explanations with implementation examples and serving-system design considerations.What You Will ExploreInference fundamentals: Trace the request lifecycle and understand the different computational characteristics of prefill and decode.Memory budgeting: Work through model-weight and KV-cache estimates, including the effects of context length, KV-head count, precision, and concurrent sequences.Attention and memory management: Explore PagedAttention, non-contiguous KV allocation, and the relationship between attention computation and memory access.Quantization: Examine weight and KV-cache precision choices, including FP8 and low-bit weight-quantization approaches.Serving architecture: Study continuous batching, request scheduling, multi-GPU execution, and latency and throughput metrics.Kernel development: Explore CUDA and Triton concepts, kernel fusion, and a quantized matrix-multiplication case study.The book includes numerical examples, reference code, and an educational asynchronous serving simulator. These examples are intended to explain mechanisms and trade-offs—not to replace hardware-specific profiling or production validation.Read the sample to review the mathematical level, coding style, and scope before purchasing.

A dense, structural data ledger mapping a single legendary landscape into a highly calculated multi-vessel alternative rock theatre script. This technical archive isolates and tracks eight distinct character registers across 25 pages of unvarnished source text. Locked and verified under the strict human-authorship guidelines of the Bleach Protocol, it serves as a permanent architectural reference for independent curators, digital archivers, and media developers. 

Nine small LangGraph agents, each adding one guardrail: PII, financial actions, risk routing, human approval, memory, retrieval, plans, output and cumulative limits. Plain Python, fully tested, no theory.

Something has been learned. The distinction holds. The model improves. The result survives examination. Then another question appears: What did we not earn by learning it? Substantive examines the difference between knowledge depth and awareness depth — between what has become known and whether the changing perimeter of that knowledge remains visible. It is not an argument against confidence, expertise, or settlement. It asks whether an earned result can remain the size of what actually earned it. Here and Now!

​A system-first engineering guide to building, deploying, operating, and securing production-grade Kubernetes clusters, cloud-native platforms, and AI inference workloads.