Book III - Deep Learning from Third Principles (Paperback)
Idioma: inglés
Editorial: Independently Published, 2026
- Tapa blanda
- Nuevo
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Vendedor de AbeBooks desde el 12 de octubre de 2005
Condición: Nuevo
EUR 21,73
Cantidad disponible: 1 disponibles
Añadir al carritoDescripción del artículo del vendedor
Paperback. Deep learning is powerful. But power without judgment can become confusion.Book III - Deep Learning from Third Principles: Data, Objectives, Evaluation, and Responsible Judgment is a calm, practical, first-principles guide for non-technical readers who want to understand deep learning beyond formulas, tools, and impressive model scores.This book does not rush you into coding. It does not assume you already understand data science, machine learning, mathematics, or artificial intelligence. Instead, it begins with the question every thoughtful builder, learner, manager, student, teacher, founder, or decision-maker must learn to ask: Are we solving the right problem, with the right data, for the right purpose?In Book I, the reader learned what it means for a system to learn. In Book II, the reader entered the inner mechanism: neurons, layers, weights, loss, gradients, and training loops. Now Book III moves into the judgment layer: the real-world space where deep learning projects succeed, fail, mislead, or responsibly serve people.Here, the reader learns how to think before building.You will learn why data is not the whole world, why labels carry human judgment, why accuracy is not always enough, why a high confidence score can still be wrong, why a model can improve on paper while failing in real use, and why sometimes the wisest deep learning decision is not to use deep learning at all.Written in simple, layered language, this book helps non-technical readers understand: What makes a problem suitable for deep learningHow to separate a real problem from a vague wishWhy data quality matters more than data size aloneHow labels shape what a model learnsWhy objectives quietly control model behaviorHow evaluation should earn trust, not decorate a dashboardWhy accuracy, precision, recall, false positives, and false negatives matterHow data leakage, bias, drift, and overconfidence create hidden riskWhen human review is necessaryWhen a simpler method may be safer, clearer, and more responsibleBook III is built for readers who want confidence without pretending. It explains deep learning judgment through everyday examples, dialogues, mind maps, reflective poetry, builder checklists, and practical thinking exercises. The goal is not to make the reader sound technical. The goal is to help the reader think clearly when powerful tools enter real decisions.This book is especially useful for beginners, students, non-technical professionals, educators, founders, product thinkers, managers, creators, and curious readers who want to understand artificial intelligence responsibly before trusting or applying it.The Value Edition at the end turns the whole book into a practical thinking workshop. It includes scratch-layer revision, brain training, math-fear removal, problem chunking, decision checklists, use-case labs, and responsible builder tools so the reader can carry the ideas into real conversations and projects.Deep learning is not only about models.It is about questions.It is about evidence.It is about human consequences.It is about knowing when to build, when to pause, and when to refuse.If you want a gentle but serious guide that teaches deep learning judgment from the ground up, this book gives you a slow, clear, and responsible path forward. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…
N° de ref. del artículo 9798185669570
- Título
- Book III - Deep Learning from Third Principles (Paperback)
- Autor
- Ravindra Kumar Nayak
- Editorial
- Independently Published
- Año de publicación
- 2026
- Estado
- new
- Encuadernación
- Paperback
- Idioma
- inglés
- ISBN 13
- 9798185669570
- Serie
- Libro 3 de 5: Learning Deep Learning Slowly A First, Second, and Third Principles Journey into Modern Intelligence
Book III — Deep Learning from Third Principles: Data, Objectives, Evaluation, and Responsible Judgment is a calm, practical, first-principles guide for non-technical readers who want to understand deep learning beyond formulas, tools, and impressive model scores.
This book does not rush you into coding. It does not assume you already understand data science, machine learning, mathematics, or artificial intelligence. Instead, it begins with the question every thoughtful builder, learner, manager, student, teacher, founder, or decision-maker must learn to ask:
Are we solving the right problem, with the right data, for the right purpose?
In Book I, the reader learned what it means for a system to learn. In Book II, the reader entered the inner mechanism: neurons, layers, weights, loss, gradients, and training loops. Now Book III moves into the judgment layer: the real-world space where deep learning projects succeed, fail, mislead, or responsibly serve people.
Here, the reader learns how to think before building.
You will learn why data is not the whole world, why labels carry human judgment, why accuracy is not always enough, why a high confidence score can still be wrong, why a model can improve on paper while failing in real use, and why sometimes the wisest deep learning decision is not to use deep learning at all.
Written in simple, layered language, this book helps non-technical readers understand:
What makes a problem suitable for deep learning
How to separate a real problem from a vague wish
Why data quality matters more than data size alone
How labels shape what a model learns
Why objectives quietly control model behavior
How evaluation should earn trust, not decorate a dashboard
Why accuracy, precision, recall, false positives, and false negatives matter
How data leakage, bias, drift, and overconfidence create hidden risk
When human review is necessary
When a simpler method may be safer, clearer, and more responsible
Book III is built for readers who want confidence without pretending. It explains deep learning judgment through everyday examples, dialogues, mind maps, reflective poetry, builder checklists, and practical thinking exercises. The goal is not to make the reader sound technical. The goal is to help the reader think clearly when powerful tools enter real decisions.
This book is especially useful for beginners, students, non-technical professionals, educators, founders, product thinkers, managers, creators, and curious readers who want to understand artificial intelligence responsibly before trusting or applying it.
The Value Edition at the end turns the whole book into a practical thinking workshop. It includes scratch-layer revision, brain training, math-fear removal, problem chunking, decision checklists, use-case labs, and responsible builder tools so the reader can carry the ideas into real conversations and projects.
Deep learning is not only about models.
It is about questions.
It is about evidence.
It is about human consequences.
It is about knowing when to build, when to pause, and when to refuse.
If you want a gentle but serious guide that teaches deep learning judgment from the ground up, this book gives you a slow, clear, and responsible path forward.
“Sinopsis” puede pertenecer a otra edición de este título.
Grand Eagle Retail
Bensenville, IL, Estados Unidos de America
Vendedor de AbeBooks desde el 12 de octubre de 2005
Tarifas de envío en Estados Unidos de America
| Artículo | De 6 a 14 días hábiles | De 6 a 16 días hábiles |
|---|---|---|
| Primer artículo | EUR 0,00 | EUR 0,00 |
Métodos de pago
Información empresarial del vendedor
APOLLO ONLINE CORP.
605 Geddes Street
Wilmington, DE Estados Unidos de America 19805
Condiciones de venta
We guarantee the condition of every book as it¿s described on the Abebooks web sites. If you¿ve changed
your mind about a book that you¿ve ordered, please use the Ask bookseller a question link to contact us
and we¿ll respond within 2 business days.
Books ship from California and Michigan.
Derecho al desistimiento
Si es un consumidor, puede rescindir el contrato de acuerdo con lo siguiente. Por consumidor se entiende cualquier persona física que actúe con fines ajenos a su actividad comercial, empresarial, oficio o profesión.
Información sobre el derecho de desistimiento
Derecho legal de desistimiento
Tiene derecho a rescindir este contrato en un plazo de 14 días sin dar ningún motivo.
El periodo de desistimiento vencerá a los 14 días desde que usted, o un tercero que no sea el transportista e indicado por usted, adquiera la posesión física del último bien o del último lote o pieza.
Para ejercer el derecho de desistimiento, complete de forma electrónica y envíe una declaración clara en nuestro sitio web, desde "Mis compras" en "Mi cuenta". Le enviaremos sin demora un acuse de recibo de dicho desistimiento a través de un soporte duradero (por ejemplo, por correo electrónico).
Para cumplir con el plazo de desistimiento, basta con que envíe su comunicación relativa al ejercicio del derecho de desistimiento antes de que venza el periodo de desistimiento.
Efectos del desistimiento
Si rescinde este contrato, le reembolsaremos todos los pagos que hayamos recibido de usted, incluidos los gastos de envío (excepto los gastos adicionales que surjan si elige un tipo de envío que no sea el tipo de envío estándar más económico que ofrecemos).
Podemos hacer una deducción del reembolso por la pérdida de valor de cualquier bien suministrado, si la pérdida es el resultado de una manipulación innecesaria por su parte.
Efectuaremos el reembolso sin demoras indebidas y, a más tardar, 14 días después de que se nos informe de su decisión de rescindir este contrato.
Efectuaremos el reembolso utilizando el mismo medio de pago que utilizó para la transacción inicial, a menos que haya acordado expresamente lo contrario; en cualquier caso, no incurrirá en ningún cargo como resultado de dicho reembolso.
Podremos retener el reembolso hasta que hayamos recibido los bienes o hasta que nos haya presentado una prueba de que los ha devuelto, lo que ocurra primero.
Deberá devolver los bienes o entregarlos a Grand Eagle Retail, Bensenville, Illinois, U.S.A., sin demoras indebidas y, en cualquier caso, en un plazo máximo de 14 días a partir del día en que nos comunique su desistimiento del presente contrato. El plazo se cumple si devuelve la mercancía antes de que venza el periodo de 14 días. Tendrá que asumir los gastos directos de devolución de los bienes. Usted solo es responsable de la disminución del valor de los bienes como resultado de una manipulación distinta a la necesaria para establecer la naturaleza, las características y el funcionamiento de los bienes.
Excepciones al derecho de desistimiento
El derecho de desistimiento no se aplica a lo siguiente:
- La entrega de periódicos, diarios o revistas, con la excepción de los contratos de suscripción; y
- El suministro de contenido digital que no se proporcione en un soporte tangible (por ejemplo, en un CD o DVD) si, al hacer el pedido, aceptó que podíamos empezar a entregarlo y que no podría desistir una vez iniciada la entrega.
Condiciones de envío
Orders usually ship within 2 business days. All books within the US ship free of charge. Delivery is 4-14 business days anywhere in the United States.
Books ship from California and Michigan.
If your book order is heavy or oversized, we may contact you to let you know extra shipping is required.