Read Anywhere and on Any Device!

Special Offer | $0.00

Join Today And Start a 30-Day Free Trial and Get Exclusive Member Benefits to Access Millions Books for Free!

Read Anywhere and on Any Device!

  • Download on iOS
  • Download on Android
  • Download on iOS

MLOps IN PRACTICE

Diego Rodrigues
4.9/5 (25903 ratings)
Description:MLOps IN PRACTICE is an essential guide for professionals looking to take Machine Learning models from experimentation to production with efficiency, scalability, and continuous automation. In this book, you will learn how to implement robust pipelines, monitor AI models in real time, and apply the best MLOps practices to ensure performance, reliability, and governance in Artificial Intelligence projects. 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. Throughout the chapters, you will explore essential frameworks and tools such as Docker, Kubernetes, CI/CD for Machine Learning, MLflow, TensorFlow Extended (TFX), FastAPI, and more. You will learn how to: Automate and scale Machine Learning pipelines with advanced versioning and monitoring techniques. Implement CI/CD for AI models, ensuring continuous training, deployment, and retraining. Manage models in production by applying observability, traceability, and bias mitigation practices. Utilize leading industry tools such as Kubeflow, MLflow, Airflow, and TFX to orchestrate ML workflows. Enhance AI governance and security, ensuring compliance with regulations and international standards. With practical examples, case studies, and established frameworks, MasterTech: MLOps in Practice is not just a technical manual—it is an indispensable resource for data scientists, ML engineers, software architects, and technology leaders looking to implement MLOps strategically and at scale. Get ready to revolutionize the way you manage AI models in production and master the most advanced MLOps techniques in 2025! TAGS: Python Java Linux Kali HTML ASP.NET Ada Assembly BASIC Borland Delphi C C# C++ CSS Cobol Compilers DHTML Fortran General JavaScript LISP PHP Pascal Perl Prolog RPG Ruby SQL Swift UML Elixir Haskell VBScript Visual Basic XHTML XML XSL Django Flask Ruby on Rails Angular React Vue.js Node.js Laravel Spring Hibernate .NET Core Express.js TensorFlow PyTorch Jupyter Notebook Keras Bootstrap Foundation jQuery SASS LESS Scala Groovy MATLAB R Objective-C Rust Go Kotlin TypeScript Dart SwiftUI Xamarin React Native NumPy Pandas SciPy Matplotlib Seaborn D3.js OpenCV NLTK PySpark BeautifulSoup Scikit-learn XGBoost CatBoost LightGBM FastAPI Redis RabbitMQ Kubernetes Docker Jenkins Terraform Ansible Vagrant GitHub GitLab CircleCI Regression Logistic Regression Decision Trees Random Forests AI ML K-Means Clustering Support Vector Machines Gradient Boosting Neural Networks LSTMs CNNs GANs ANDROID IOS MACOS WINDOWS Nmap Metasploit Framework Wireshark Aircrack-ng John the Ripper Burp Suite SQLmap Maltego Autopsy Volatility IDA Pro OllyDbg YARA Snort ClamAV Netcat Tcpdump Foremost Cuckoo Sandbox Fierce HTTrack Kismet Hydra Nikto OpenVAS Nessus ZAP Radare2 Binwalk GDB OWASP Amass Dnsenum Dirbuster Wpscan Responder Setoolkit Searchsploit Recon-ng BeEF AWS Google Cloud IBM Azure Databricks Nvidia Meta Power BI IoT CI/CD Hadoop Spark Dask SQLAlchemy Web Scraping MySQL Big Data Science OpenAI ChatGPT Handler RunOnUiThread() Qiskit Q# Cassandra Bigtable VIRUS MALWARE Information Pen Test Cybersecurity Linux Distributions Ethical Hacking Vulnerability Analysis System Exploration Wireless Attacks Web Application Security Malware Analysis Social Engineering Social Engineering Toolkit SET Computer Science IT Professionals Careers Expertise Library Training Operating Systems Security Testing Penetration Test Cycle Mobile Techniques Industry Global Trends Tools Framework Network Security Courses Tutorials Challenges Landscape Cloud Threats Compliance Research Technology Flutter Ionic Web Views Capacitor APIs REST GraphQL Firebase Redux Provider Bitrise Actions Material Design Cupertino Fastlane Appium Selenium Jest Visual Studio AR VR sql deepseek mysql startup digital marketingWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with MLOps IN PRACTICE. To get started finding MLOps IN PRACTICE, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.
Pages
153
Format
PDF, EPUB & Kindle Edition
Publisher
StudioD21
Release
2025
ISBN
WN9FEQAAQBAJ

MLOps IN PRACTICE

Diego Rodrigues
4.4/5 (1290744 ratings)
Description: MLOps IN PRACTICE is an essential guide for professionals looking to take Machine Learning models from experimentation to production with efficiency, scalability, and continuous automation. In this book, you will learn how to implement robust pipelines, monitor AI models in real time, and apply the best MLOps practices to ensure performance, reliability, and governance in Artificial Intelligence projects. 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. Throughout the chapters, you will explore essential frameworks and tools such as Docker, Kubernetes, CI/CD for Machine Learning, MLflow, TensorFlow Extended (TFX), FastAPI, and more. You will learn how to: Automate and scale Machine Learning pipelines with advanced versioning and monitoring techniques. Implement CI/CD for AI models, ensuring continuous training, deployment, and retraining. Manage models in production by applying observability, traceability, and bias mitigation practices. Utilize leading industry tools such as Kubeflow, MLflow, Airflow, and TFX to orchestrate ML workflows. Enhance AI governance and security, ensuring compliance with regulations and international standards. With practical examples, case studies, and established frameworks, MasterTech: MLOps in Practice is not just a technical manual—it is an indispensable resource for data scientists, ML engineers, software architects, and technology leaders looking to implement MLOps strategically and at scale. Get ready to revolutionize the way you manage AI models in production and master the most advanced MLOps techniques in 2025! TAGS: Python Java Linux Kali HTML ASP.NET Ada Assembly BASIC Borland Delphi C C# C++ CSS Cobol Compilers DHTML Fortran General JavaScript LISP PHP Pascal Perl Prolog RPG Ruby SQL Swift UML Elixir Haskell VBScript Visual Basic XHTML XML XSL Django Flask Ruby on Rails Angular React Vue.js Node.js Laravel Spring Hibernate .NET Core Express.js TensorFlow PyTorch Jupyter Notebook Keras Bootstrap Foundation jQuery SASS LESS Scala Groovy MATLAB R Objective-C Rust Go Kotlin TypeScript Dart SwiftUI Xamarin React Native NumPy Pandas SciPy Matplotlib Seaborn D3.js OpenCV NLTK PySpark BeautifulSoup Scikit-learn XGBoost CatBoost LightGBM FastAPI Redis RabbitMQ Kubernetes Docker Jenkins Terraform Ansible Vagrant GitHub GitLab CircleCI Regression Logistic Regression Decision Trees Random Forests AI ML K-Means Clustering Support Vector Machines Gradient Boosting Neural Networks LSTMs CNNs GANs ANDROID IOS MACOS WINDOWS Nmap Metasploit Framework Wireshark Aircrack-ng John the Ripper Burp Suite SQLmap Maltego Autopsy Volatility IDA Pro OllyDbg YARA Snort ClamAV Netcat Tcpdump Foremost Cuckoo Sandbox Fierce HTTrack Kismet Hydra Nikto OpenVAS Nessus ZAP Radare2 Binwalk GDB OWASP Amass Dnsenum Dirbuster Wpscan Responder Setoolkit Searchsploit Recon-ng BeEF AWS Google Cloud IBM Azure Databricks Nvidia Meta Power BI IoT CI/CD Hadoop Spark Dask SQLAlchemy Web Scraping MySQL Big Data Science OpenAI ChatGPT Handler RunOnUiThread() Qiskit Q# Cassandra Bigtable VIRUS MALWARE Information Pen Test Cybersecurity Linux Distributions Ethical Hacking Vulnerability Analysis System Exploration Wireless Attacks Web Application Security Malware Analysis Social Engineering Social Engineering Toolkit SET Computer Science IT Professionals Careers Expertise Library Training Operating Systems Security Testing Penetration Test Cycle Mobile Techniques Industry Global Trends Tools Framework Network Security Courses Tutorials Challenges Landscape Cloud Threats Compliance Research Technology Flutter Ionic Web Views Capacitor APIs REST GraphQL Firebase Redux Provider Bitrise Actions Material Design Cupertino Fastlane Appium Selenium Jest Visual Studio AR VR sql deepseek mysql startup digital marketingWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with MLOps IN PRACTICE. To get started finding MLOps IN PRACTICE, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.
Pages
153
Format
PDF, EPUB & Kindle Edition
Publisher
StudioD21
Release
2025
ISBN
WN9FEQAAQBAJ

More Books

loader