Machine Learning with Microsoft ML.Net: Develop Machine Learning Models with ML.NET from the Developer's perspective

Learn how to use ML.NET, the open source and cross-platform machine learning framework ML.NET, that help us to build custom machine learning models and integrate them into our apps. Key Features You will learn to create new ML models for your applications You’ll also use Open Neural Network Exchange (ONNX) models You will know how to manage the lifecycle of model in your applications You will understand how to use ML.NET in enterprise solutions Book DescriptionThe world of artificial intelligence has evolved a lot in recent years. And one field that has evolved in an incredible way is machine learning. Machine learning takes its meaning from the concept that a computer program can learn and adapt to new data without human interference. Over time, the tools available to developers have also evolved in this field. One of them is ML.NET, an open source and cross-platform machine learning framework that helps .NET developer to integrate machine learning into their applications. This book begins by introducing what the world of machine learning is and how ML.NET can help the developer in the integration of machine learning models into their applications. The book accompanies the reader in what are real examples. In doing so, the reader can understand how to identify the correct scenario with which to train their machine learning model or reuse models already trained by other libraries within their applications. At the end, following the path of examples, the reader can get an idea of what are enterprise concepts and how to use the framework in the most correct way possible.What you will learn Create innovative application that includes ML models. Learn to provide a set of new use case of the framework. Understand Model Lifecycle. Analyze the model generation methods made available (API, Model Builder, cli) to understand in which scenarios to use. Discover how to integrate ML models within a .NET application and understand which ML algorithm to use to achieve our goal. Who this book is forThis book is for all developers who want to understand how to evolve their applications by including advanced machine learning models. The reader will have to know the basic concepts of software development. They do not need to have experience in the world of developing machine learning models or algorithms.

Table of Contents:
Table of Contents Getting Started with machine learning and ML.NET Deep dive the framework Deep Learning or Machine Learning ML.NET AutoML API Text Classification with ML.NET Text analysis with BERT and ML.NET Regression with ML.NET Time Series Forecasting with ML.NET Deep learning with ML.NET Object detection with ML.NET Azure ML with ML.NET Model Explainability with ML.NET MLOPS with ML.NET Create a real Enterprise ML.NET use case

About the Author :
Marco Zamana is a Cloud Solution Architect Engineering at Microsoft. He is a skilled Cloud Solution Architect and a .NET Developer, who applies broad technical, industry, and enterprise knowledge to architecture projects to meet business and information technology (IT) requirements. He creates and sustains constructive tension and trust with customers/partners by respectfully challenging their decisions, and acts as a mentor to junior colleagues by educating them on technical and non-technical concepts and sharing best practices. He is the President and Co-Founder of CloudGen Verona which is a non profit association.