Machine Learning — Teaching Machines to Learn下载-CSDN社区

Machine Learning — Teaching Machines to Learn – Good Audience

Machine Learning by Tutorials: Beginning machine learning for Apple and iOS by Matthijs Hollemans-- May 31, 2019 Machine Learning by Tutorials: Beginning machine learning for Apple and iOS by Matthijs Hollemans English | 2019 | ISBN: 1942878582 | 539 Pages | True PDF, EPUB, CODE | 695 MB Learn Machine Learning! Machine learning is one of those topics that can be daunting at first blush. It’s not clear where to start, what path someone should take and what APIs to learn in order to get started teaching machines how to learn. This is where Machine Learning by Tutorials comes in! In this book, we’ll hold your hand through a number of tutorials, to get you started in the world of machine learning. We’ll cover a wide range of popular topics in the field of machine learning, while developing apps that work on iOS devices. This books is for the intermediate iOS developer who already knows the basics of iOS and Swift development, but wants to understand how machine learning works. Topics covered in Machine Learning by Tutorials CoreML: Learn how to add a machine learning model to your iOS apps, and how to use iOS APIs to access it. Create ML: Learn how to create your own model using Apple’s Create ML Tool. Turi Create and Keras: Learn how to tune parameters to improve your machine learning model using more advanced tools. Image Classification: Learn how to apply machine learning models to predict objects in an image. Convolutional Networks: Learn advanced machine learning techniques for predicting objects in an image with Convolutional Neural Networks (CNNs). Sequence Classification: Learn how you can use recurrent neural networks (RNNs) to classify motion from an iPhone’s motion sensor. Text-to-text Transform: Learn to how machine learning can be used to convert bodies of text between two languages.

Key Features, Learn advanced techniques in deep learning with this example-rich guide on Google's brainchildExplore various neural networks with the help of this comprehensive guideAdvanced guide on machine learning techniques, in particular TensorFlow for deep learning., Book Description, Deep learning is the next step after machine learning. It is machine learning but with a more advanced implementation. As machine learning is no longer an academic topic, but a mainstream practice, deep learning has taken a front seat. With deep learning being used by many data scientists, deeper neural networks are evaluated for accurate results. Data scientists want to explore data abstraction layers and this book will be their guide on this journey. This book evaluates common, and not so common, deep neural networks and shows how these can be exploited in the real world with complex raw data using TensorFlow., The book will take you through an understanding of the current machine learning landscape then delve into TensorFlow and how to use it by considering various data sets and use cases. Throughout the chapters, you'll learn how to implement various deep learning algorithms for your machine learning systems and integrate them into your product offerings such as search, image recognition, and language processing. Additionally, we'll examine its performance by optimizing it with respect to its various parameters, comparing it against benchmarks along with teaching machines to learn from the information and determine the ideal behavior within a specific context, in order to maximize its performance., After finishing the book, you will be familiar with machine learning techniques, in particular TensorFlow for deep learning, and will be ready to apply some of your knowledge in a real project either in a research or commercial setting., What you will learn, Provide an overview of the machine learning landscapeLook at the historical development and progress of deep learningDescribe TensorFlow and become very familiar with it both in theory and in practiceAccess public datasets and use TF to load, process, clean, and transform dataUse TensorFlow on real-world data sets including images and textGet familiar with TensorFlow by applying it in various hands on exercises using the command lineEvaluate the performance of your deep learning modelsQuickly teach machines to learn from data by exploring reinforcement learning techniques.Understand how this technology is being used in the real world by exploring active areas of deep learning research and application.