内容推荐 深度学习往往被视为数学博士和大型科技公司的专属领域。但正如这本实践指南所展示的那样,熟练使用Python的程序员只需很少的数学背景、少量的数据和最少的代码,就可以在深度学习方面取得令人印象深刻的成果。怎么样才能做到?使用fastai,这是首个为最常用的深度学习应用提供一致接口的库。 本书作者Jeremy Howard和Sylvain Gugger是fastai的创建者,他们向你展示了如何使用fastai和PyTorch在各种任务上训练一个模型。你还将逐步深入了解深度学习理论,以便充分理解幕后的算法。 在计算机视觉、自然语言处理、表格型数据和协同过滤中训练模型; 学习在实践中至关重要的最新深度学习技术; 通过了解深度学习模型的工作原理,提高准确性、速度和可靠性; 了解如何将你的模型转化为Web应用; 从头开始实现深度学习算法; 考虑你的工作所带来的道德影响; 从PyTorch联合创始人Soumith Chintala的前言中获得启示。 目录 Preface Foreword Part I. Deep Learning in Practice 1. Your Deep Learning Journey Deep Learning Is for Everyone Neural Networks: A Brief History Who We Are How to Learn Deep Learning Your Projects and Your Mindset The Software: PyTorch, fastai, and Jupyter (And Why It Doesn't Matter) Your First Model Getting a GPU Deep Learning Server Running Your First Notebook What Is Machine Learning? What Is a Neural Network? A Bit of Deep Learning Jargon Limitations Inherent to Machine Learning How Our Image Recognizer Works What Our Image Recognizer Learned Image Recognizers Can Tackle Non-Image Tasks Jargon Recap Deep Learning Is Not Just for Image Classification Validation Sets and Test Sets Use Judgment in Defining Test Sets A Choose Your Own Adventure Moment Questionnaire Further Research 2. From Model to Production The Practice of Deep Learning Starting Your Project The State of Deep Learning The Drivetrain Approach Gathering Data From Data to DataLoaders Data Augmentation Training Your Model, and Using It to Clean Your Data Turning Your Model into an Online Application Using the Model for Inference Creating a Notebook App from the Model Turning Your Notebook into a Real App Deploying Your App How to Avoid Disaster Unforeseen Consequences and Feedback Loops Get Writing! Questionnaire Further Research 3. Data Ethics Key Examples for Data Ethics Bugs and Recourse: Buggy Algorithm Used for Healthcare Benefits Feedback Loops: YouTube's Recommendation System Bias: Professor Latanya Sweeney "Arrested" Why Does This Matter? Integrating Machine Learning with Product Design Topics in Data Ethics Recourse and Accountability Feedback Loops Bias Disinformation Identifying and Addressing Ethical Issues Analyze a Project You Are Working On Processes to Implement The Power of Diversity …… Part II. Understanding fastai's applications Part III. Foundations of Deep Learning Part IV. Deep learning from Scratch Index |