[center]Automated Machine Learning with AutoKeras | 520 | Luis Sobrecueva | Packt Publishing | 9781800567641[/align]
✅ Create better and easy-to-use deep learning models with AutoKeras
Key Features ✔Design and implement your own custom machine learning models using the features of AutoKeras
✔Learn how to use AutoKeras for techniques such as classification, regression, and sentiment analysis
✔Get familiar with advanced concepts as multi-modal, multi-task, and search space customization
Book Description AutoKeras is an AutoML open-source software library that provides easy access to deep learning models. If you are looking to build deep learning model architectures and perform parameter tuning automatically using AutoKeras, then this book is for you.
This book teaches you how to develop and use state-of-the-art AI algorithms in your projects. It begins with a high-level introduction to automated machine learning, explaining all the concepts required to get started with this machine learning approach. You will then learn how to use AutoKeras for image and text classification and regression. As you make progress, you'll discover how to use AutoKeras to perform sentiment analysis on documents. This book will also show you how to implement a custom model for topic classification with AutoKeras. Toward the end, you will explore advanced concepts of AutoKeras such as working with multi-modal data and multi-task, customizing the model with AutoModel, and visualizing experiment results using AutoKeras Extensions.
By the end of this machine learning book, you will be able to confidently use AutoKeras to design your own custom machine learning models in your company.
What you will learn ✔Set up a deep learning workstation with TensorFlow and AutoKeras
✔Automate a machine learning pipeline with AutoKeras
✔Create and implement image and text classifiers and regressors using AutoKeras
✔Use AutoKeras to perform sentiment analysis of a text, classifying it as negative or positive
✔Leverage AutoKeras to classify documents by topics
✔Make the most of AutoKeras by using its most powerful extensions
Who this book is for This book is for machine learning and deep learning enthusiasts who want to apply automated ML techniques to their projects. Prior basic knowledge of Python programming and machine learning is expected to get the most out of this book.
Discover the world of Artificial Intelligence (AI) and Machine Learning (ML) through the lens of Microsoft Excel with our comprehensive ebook. Dive deep into the fundamentals of AI, exploring topics such as the difference between Traditional Programming and AI, Abstraction, Action Language, and Adaptive Algorithms.
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Explore advanced functionalities of Microsoft Excel, including Conditional Formatting, Heatmaps, and Decision Boundaries, and understand how they can be applied in the realm of AI. Delve into Natural Language Processing, Sentiment Analysis, and Data Mining using Excel functions like CORREL, FIND, and INDIRECT.
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Navigate through the intricacies of Data Cleaning, Imputation, and Regression Imputation, and grasp the importance of Knowledge Engineering in the AI landscape. Learn about Machine Learning concepts such as Error-driven Learning, Neural Networks, and Perceptron, all within the familiar environment of Microsoft Excel.
From Tokenization to Natural Language Generation (NLG), this guide covers a wide spectrum of AI topics. Understand the significance of AI Ethics, including beneficence, justice, non-maleficence, privacy, responsibility, and transparency.
Whether you are a student, professional, or AI enthusiast, "Learning the Basics of Artificial Intelligence (AI) using Microsoft Excel" empowers you to apply AI concepts practically, using the tools you already know. Embrace the future of technology and elevate your skills with this indispensable resource.
✅ Contents of download скачать:
⭐️ Machine Learning in Python for Everyone.pdf (35.46 MB)
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✅ Machine Learning in Python for Everyone (35.46 MB)
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