Machine Learning & Big Data Bundle 2nd Edition
Multiple file types
Tier 1 - Pay £1.00
Tier 2 - Pay £8.00 - Including products above
Tier 3 - Pay £19.99 - Including products above
Get up and running with machine learning life cycle management and implement MLOps in your organization
- Become well-versed with MLOps techniques to monitor the quality of machine learning models in the production
- Explore a monitoring framework for ML models in production and learn about end-to-end traceability for deployed models
- Perform CI/CD to automate new implementations in ML pipelines
MLOps is a systematic approach to building, deploying, and monitoring machine learning (ML) solutions. It is an engineering discipline that can be applied to various industries and use cases. This book presents comprehensive insights into MLOps coupled with real-world examples to help you to write programs, train robust and scalable ML models, and build ML pipelines to train and deploy models securely in production.
The book begins by familiarizing you with the MLOps workflow so you can start writing programs to train ML models. Then you'll then move on to explore options for serializing and packaging ML models post-training to deploy them to facilitate machine learning inference, model interoperability, and end-to-end model traceability. You'll understand how to build ML pipelines, continuous integration, and continuous delivery (CI/CD) pipelines, and monitoring pipelines to systematically build, deploy, monitor, and govern ML solutions for businesses and industries. Finally, you'll apply the knowledge you've gained to build real-world projects.
By the end of this ML book, you'll have a 360-degree view of MLOps and be ready to implement MLOps in your organization.
What you will learn
- Formulate data governance strategies and pipelines for ML training and deployment
- Get to grips with implementing ML pipelines, CI/CD pipelines, and ML monitoring pipelines
- Design a robust and scalable microservice and API for test and production environments
- Curate your custom CD processes for related use cases and organizations
- Monitor ML models, including monitoring data drift, model drift, and application performance
- Build and maintain automated ML systems
Who this book is for
This MLOps book is for data scientists, software engineers, DevOps engineers, machine learning engineers, and business and technology leaders who want to build, deploy, and maintain ML systems in production using MLOps principles and techniques. Basic knowledge of machine learning is necessary to get started with this book.
About this Bundle
Navigate the complex world of processing Big Data to get machines to do the tasks for you! Learn how to automate with 20 eBooks in the brand-new Machine Learning & Big Data Bundle 2nd Edition
With seven all-new-to-Fanatical eBooks and twenty included across three tiers, you’ll get a deep dive into major computing software and services including Python, Azure, Amazon services, and much more.
Tier 1 features four products, including the easy-to-follow Engineering MLOps and the all-new Serverless Analytics with Amazon Athena.
This eBook will help you with an overview of the serverless analytics experience offered by Athena and teaches you how to build and tune an S3 Data Lake using Athena.
Why not up the ante and choose Tier 2? Here you’ll receive a total of twelve eBooks to help you gain new skills and improve on the ones you’ve already started learning.
With the Azure Databricks Cookbook, you’ll be able to get to grips with building and productionizing end-to-end big data solutions in Azure and learning vital best practices.
Use TensorFlow Enterprise with other GCP services to improve the speed and efficiency of machine learning pipelines with Learn TensorFlow Enterprise and discover how to build a cloud-based data warehouse at petabyte-scale that is burstable and built to scale for end-to-end analytical solutions with Amazon Redshift Cookbook.
Or get the full works and choose Tier 3 to obtain all 20 eBooks available. Leverage DataRobot's enterprise AI platform and automated decision intelligence to extract business value from data with Agile Machine Learning with DataRobot.
Discover how TPOT can be used to handle automation in machine learning and explore the different types of tasks found in Machine Learning Automation with TPOT and the Python Natural Language Processing Cookbook will take you through how to get to grips with solving real-world NLP problems, such as dependency parsing, information extraction, topic modeling and so on.
All these and much more are here in our new & updated Machine Learning & Big Data Bundle 2nd Edition
Please note that the eBooks in this collection vary in format (EPUB & PDF)