Build highly secure and scalable machine learning platforms to support the fast-paced adoption of machine learning solutionsKey FeaturesExplore different ML tools and frameworks to solve large-scale machine learning challenges in the cloudBuild an efficient data science environment for data exploration, model building, and model trainingLearn how to implement bias detection, privacy, and explainability in ML model developmentBook DescriptionWhen equipped with a highly scalable machine learning (ML) platform, organizations can quickly scale the delivery of ML products for faster business value realization. There is a huge demand for skilled ML solutions architects in different industries, and this handbook will help you master the design patterns, architectural considerations, and the latest technology insights you'll need to become one.You'll start by understanding ML fundamentals and how ML can be applied to solve real-world business problems. Once you've explored a few leading problem-solving ML algorithms, this book will help you tackle data management and get the most out of ML libraries such as TensorFlow and PyTorch.Using open source technology such as Kubernetes/Kubeflow to build a data science environment and ML pipelines will be covered next, before moving on to building an enterprise ML architecture using Amazon Web Services (AWS). You'll also learn about security and governance considerations, advanced ML engineering techniques, and how to apply bias detection, explainability, and privacy in ML model development. And finally, you'll get acquainted with AWS AI services and their applications in real-world use cases.By the end of this book, you'll be able to design and build an ML platform to support common use cases and architecture patterns like a true professional.What you will learnApply ML methodologies to solve business problemsDesign a practical enterprise ML platform architectureImplement MLOps for ML workflow automationBuild an end-to-end data management architecture using AWSTrain large-scale ML models and optimize model inference latencyCreate a business application using an AI service and a custom ML modelUse AWS services to detect data and model bias and explain modelsWho this book is forThis book is for data scientists, data engineers, cloud architects, and machine learning enthusiasts who want to become machine learning solutions architects. You'll need basic knowledge of the Python programming language, AWS, linear algebra, probability, and networking concepts before you get started with this handbook.Table of ContentsMachine Learning and Machine Learning Solutions ArchitectureBusiness Use Cases for Machine LearningMachine Learning Algorithms Data Management for Machine LearningOpen Source Machine Learning LibrariesKubernetes Container Orchestration Infrastructure ManagementOpen Source Machine Learning PlatformsBuilding a Data Science Environment Using AWS ML ServicesBuilding an Enterprise ML Architecture with AWS ML ServicesAdvanced ML EngineeringML Governance, Bias, Explainability, and PrivacyBuilding ML Solutions with AWS AI Services
✔ Author(s): David Ping
✔ Title: The Machine Learning Solutions Architect Handbook: Create machine learning platforms to run solutions in an enterprise setting
✔ Rating : 4.9 out of 5 base on (41 reviews)
✔ ISBN-10: 1801072167
✔ ISBN-13: 9781801072168
✔ Language: English
✔ Format ebook: PDF, EPUB, Kindle, Audio, HTML and MOBI
✔ Device compatibles: Android, iOS, PC and Amazon Kindle
Readers' opinions about The Machine Learning Solutions Architect Handbook by David Ping
Josephine Alvarez
This book completely captured my heart. The characters were so relatable, and their journeys resonated deeply with me. The writing was poetic and powerful, leaving me with a sense of awe. I'm grateful to have experienced this literary gem.
Katherine Stevenson
This book has reignited my passion for reading. It reminded me of the sheer joy that can be found in losing oneself in the pages of a good story. I can't wait to explore more books now.
Rosa Bax
The plot twists were executed masterfully. I was left gasping at every unexpected turn, and the suspense kept me on edge throughout. Bravo to the author for keeping me guessing.
