Part of the Practical Tech Guide Series, this book focuses on what actually matters: how to take a folder of images and turn it into a working model you understand and control.
You don’t need a machine learning background. If you can run a command and open a browser, you can follow this guide from start to finish.
Inside, you’ll learn:
• What image classification is and how it works (in simple terms)
• How to prepare and organise your own image dataset
• How to train models locally on your own machine
• How to choose the right architecture (PyTorch and TensorFlow)
• How to read accuracy, loss, and training results with confidence
• How to improve your model with better data and tuning
• When to use local training vs cloud or browser-based tools
Everything is built around a simple, open-source training tool with a browser-based interface — so you can focus on results, not boilerplate code.
No deep math. No unnecessary theory. No black boxes.
Whether you're experimenting with AI, building a small project, or working with sensitive data you don’t want to upload to the cloud, this guide gives you a clear, practical path.
If you want to train AI image models locally — and actually understand what you're doing — this book is for you.
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Paperback. Condition: new. Paperback. Part of the Practical Tech Guide Series, this book focuses on what actually matters: how to take a folder of images and turn it into a working model you understand and control. You don't need a machine learning background. If you can run a command and open a browser, you can follow this guide from start to finish. Inside, you'll learn: - What image classification is and how it works (in simple terms)- How to prepare and organise your own image dataset- How to train models locally on your own machine- How to choose the right architecture (PyTorch and TensorFlow)- How to read accuracy, loss, and training results with confidence- How to improve your model with better data and tuning- When to use local training vs cloud or browser-based tools Everything is built around a simple, open-source training tool with a browser-based interface - so you can focus on results, not boilerplate code. No deep math. No unnecessary theory. No black boxes. Whether you're experimenting with AI, building a small project, or working with sensitive data you don't want to upload to the cloud, this guide gives you a clear, practical path. If you want to train AI image models locally - and actually understand what you're doing - this book is for you. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798257878367
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Taschenbuch. Condition: Neu. Neuware - Part of the Practical Tech Guide Series, this book focuses on what actually matters: how to take a folder of images and turn it into a working model you understand and control. You don't need a machine learning background. If you can run a command and open a browser, you can follow this guide from start to finish. Inside, you'll learn: - What image classification is and how it works (in simple terms)- How to prepare and organise your own image dataset- How to train models locally on your own machine- How to choose the right architecture (PyTorch and TensorFlow)- How to read accuracy, loss, and training results with confidence- How to improve your model with better data and tuning>Everything is built around a simple, open-source training tool with a browser-based interface - so you can focus on results, not boilerplate code. No deep math. No unnecessary theory. No black boxes. Whether you're experimenting with AI, building a small project, or working with sensitive data you don't want to upload to the cloud, this guide gives you a clear, practical path. If you want to train AI image models locally - and actually understand what you're doing - this book is for you. Seller Inventory # 9798257878367
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Paperback. Condition: new. Paperback. Part of the Practical Tech Guide Series, this book focuses on what actually matters: how to take a folder of images and turn it into a working model you understand and control. You don't need a machine learning background. If you can run a command and open a browser, you can follow this guide from start to finish. Inside, you'll learn: - What image classification is and how it works (in simple terms)- How to prepare and organise your own image dataset- How to train models locally on your own machine- How to choose the right architecture (PyTorch and TensorFlow)- How to read accuracy, loss, and training results with confidence- How to improve your model with better data and tuning- When to use local training vs cloud or browser-based tools Everything is built around a simple, open-source training tool with a browser-based interface - so you can focus on results, not boilerplate code. No deep math. No unnecessary theory. No black boxes. Whether you're experimenting with AI, building a small project, or working with sensitive data you don't want to upload to the cloud, this guide gives you a clear, practical path. If you want to train AI image models locally - and actually understand what you're doing - this book is for you. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798257878367
Quantity: 1 available