Exam Ref DP-100 Designing and Implementing a Data Science Solution on Azure
Dayne Sorvisto. Overall , the use of GitHub Actions combined with Azure Machine Learning creates a robust framework ... CI / CD workflows that automate critical tasks like model training , validation , and deployment , ensuring that ...
Effective Machine Learning Teams
... Azure Machine Learning , among many others . To keep this example simple and generalizable , we've opted for the simplest possible option : train the model on a CI compute instance using GitHub Actions ... CD pipeline using GitHub Actions ...
Ultimate Kubernetes for Cloud-Native Applications
... Azure DevOps ) All ML code , training workflows , and deployment configurations are stored in a Git repository hosted on platforms such as GitHub or Azure DevOps . This acts as the single source of truth for model versioning , CI / CD ...
Data Engineering with Databricks Cookbook
... (CI/CD). • You can work on data, analytics, and machine learning (ML) projects in a team-oriented environment ... learn the YAML syntax and the bundle schema to define your project's metadata • You need to install and configure the ...
Generative AI for Software Developers
... GitHub are foundational tools for version control and collaboration . Git tracks changes in source code , while GitHub provides a cloud - based ... CI/CD service that replaces 120 Version Control Tools for Generative AI App Development.
Databricks Data Intelligence Platform
... ( training and batch inference jobs , etc. ) defined through Databricks CLI bundles CI / CD ( GitHub Actions or Azure DevOps ) : GitHub Actions or Azure DevOps workflows to test and deploy ML code and resources Source control Development ...
Ultimate LLMOps for LLM Engineering
... machine learning life cycle. This includes everything from data preparation and model training to deployment, monitoring, and collaboration. Version control is fundamental to MLOps, and tools like Git are ubiquitous for tracking changes ...
MLOps on Azure for Real-World AI
Only Real MLOps. Every chapter in this book was written to reflect current best practices and real tools being used by top ML engineering teams across industries. This is not another academic guide - it's a hands-on engineering playbook.
Hands-On MLOps on Azure
By the end of this book, you'll be ready to design, deploy, and maintain enterprise-grade ML solutions with confidence.
MLOps IN PRACTICE
Written by Diego Rodrigues, a best-selling author with over 180 titles published in six languages, this book combines theory and practice, offering a modern and applied approach to the current MLOps landscape.
Automating Workflows with GitHub Actions
If you are new to GitHub and GitHub Actions in general, then this book is for you. Basic knowledge of GitHub as a platform will help you to get the most out of this book.
Azure Bicep QuickStart Pro
Starting with the basics, this book walks you through the syntax of JSON and the templates available in Azure Resource Manager (ARM).
LEARN TERRAFORM
LEARN TERRAFORM Automate Multi-Cloud Infrastructure with Scalability This book is ideal for infrastructure professionals, developers, and students who want to master Terraform with practical application in cloud environments like AWS, ...
Azure for Developers
This third edition of Azure for Developers transforms complex cloud concepts into practical skills, guiding you through the design, deployment, and management of cloud-native solutions while eliminating infrastructure headaches.
Azure Cloud Projects
By the end of this book, you’ll have a solid grasp of Azure’s capabilities and a portfolio of practical projects that showcase your job-ready skills and set you up for success in entry-level cloud roles.What you will learn Set up Azure ...
Innovative Cross-Platform Solutions
By the end of this book, you'll be able to merge Python and C# effectively, building agile, scalable, and secure applications that can be deployed on multiple platforms and meet the demands of modern businesses and users.
TensorFlow Machine Learning Tutorial for Developers
From crafting high-throughput data pipelines and writing custom training loops with tf.GradientTape to applying mixed-precision, pruning, and quantization, this book transforms theory into practice.
Implementing MLOps in the Enterprise
This book will help you: Learn the MLOps process, including its technological and business value Build and structure effective MLOps pipelines Efficiently scale MLOps across your organization Explore common MLOps use cases Build MLOps ...
Dockerizing Python for Production
Beyond theory, the book is packed with hands-on examples, step-by-step walkthroughs, and practical techniques you can apply immediately. What makes this book different? It doesn't recycle generic explanations or surface-level tutorials.
Mastering Terraform
This book takes a hands-on approach to teaching Terraform, helping you build efficient cloud infrastructure using real-world scenarios and best practices.