Notes about Cutting-Edge Technologies and Everything

We know data preparation requires a ton of work and thought. In this provocative article, Hugo Bowne-Anderson provides a formal rationale for why that work matters, why data preparation is particularly important for reanalyzing data, and why you should stay focused on the question you hope to answer. Along the way, Hugo introduces how tools and automation can help augment analysts and better enable real-time models. In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. This is the garbage in, garbage out principle: flawed data going in leads to flawed results, algorithms, and business decisions. If a self-driving car’s decision-making algorithm is trained on data of traffic collected during the day, you wouldn’t put it on the roads at night. To take it a step further, if such an algorithm is trained in an environment with car...

O'Reilly's surveys over the past couple of years have shown growing interest in machine learning (ML) among organizations from diverse industries. A few factors are contributing to this strong interest in implementing ML in products and services. First, the machine learning community has conducted groundbreaking research in many areas of interest to companies, and much of this research has been conducted out in the open via preprints and conference presentations. We are also beginning to see researchers share sample code written in popular open source libraries, and some even share pre-trained models. Organizations now also have more use cases and case studies from which to draw inspiration—no matter what industry or domain you are interested in, chances are there are many interesting ML applications you can learn from. Finally, modeling tools are improving, and automation is beginning to allow new users to tackle problems that used to be the province of experts. With the s...

O’Reilly and TensorFlow are teaming up for the first-ever TensorFlow World, happening October 28–31 in Santa Clara. Where today's top minds bring machine learning to life From data centers to edge devices, and diagnosing diseases to environmental conservation, TensorFlow is powering the machine learning revolution. Growing from its origins at Google, TensorFlow is a fast-moving and expansive open source ecosystem, covering many platforms and programming languages in industry, education, and research. O'Reilly Media and TensorFlow are teaming up to present the first TensorFlow World, bringing together the entire community to explore the latest developments, from research to production, and application areas spanning healthcare, finance, robotics, IoT, and more. We'll hear how data scientists, engineers, developers, and product managers are leveraging TensorFlow to build products and services to help transform their company. Executives, CTOs, and innovators will share ...