McConnaughy, Tim

McNutt, Steve

Miles, Christopher

A pragmatic guide to acing the AWS ANS-C01 exam

AWS Certified Advanced Networking – Specialty (ANS-C01) Certification Guide

Despoudis, Theofanis

Build clean and scalable apps with proven patterns and expert insights

TypeScript 5 Design Patterns and Best Practices

Malavasi, Alexandre

A project-based guide to building web applications with ASP.NET Core 9 and JavaScript frameworks

Modern Full-Stack Web Development with ASP.NET Core

Verma, Jatin

Build a solid foundation in Snowflake to pass the SnowPro Core exam on the first attempt

SnowPro Core Certification Study Guide

Mukherjee, Amit

Casalaina, Marco

Saladi, Adithya

A practical guide to unlocking generative AI-powered innovation with Azure OpenAI

Azure OpenAI Essentials

Loredo, Robert

Write your own practical quantum programs with Python

Learn Quantum Computing with Python and IBM Quantum

Najlaa, Najihah

Master video editing with expert tips, techniques, and workflows

The Complete Guide to Adobe Premiere Pro 2025

Makhija, Jagjeet Singh

Odunukwe, Charles

Boost your skills with expert insights and certification-ready strategies for Microsoft analytics

Implementing Analytics Solutions Using Microsoft Fabric—DP-600 Exam Study Guide

Belmansour, Tidjani

Brady, Damian

A step-by-step guide to developing cross-platform CLI apps—from coding and testing to deployment

Building CLI Applications with C# and .NET

Apperson, Lem

Weinberger, Jonathan

Leverage C# scripting in Unity to create immersive games and VR experiences

Unity 6 Game Development with C# Scripting

Build a solid mathematical foundation for training efficient deep neural networks

Hands-On Mathematics for Deep Learning

<span xml:lang="en">Hands-On Mathematics for Deep Learning: Build a solid mathematical foundation for training efficient deep neural networks</span>

Dawani, Jay

A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architecturesKey FeaturesUnderstand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networksLearn the mathematical concepts needed to understand how deep learning models functionUse deep learning for solving problems related to vision, image, text, and sequence applicationsBook DescriptionMost programmers and data scientists struggle with mathematics, having either overlooked or forgotten core mathematical concepts.

A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architecturesKey...

Hands-On Mathematics for Deep Learning: Build a solid...

Hands-On Mathematics for Deep Learning: Build a solid mathematical foundation for training efficient deep neural networks

Format

Hands-On Mathematics for Deep Learning: Build a solid mathematical foundation for training efficient deep neural networks

Jay Dawani

La gente también lee