The purpose of this book is to help anyone involved in small-scale geophys- ical surveys. It is not a textbook in the traditional sense, in that it is designed for use in the field and concerns itself with practical matters – with the- ory taking second place. Where theory determines field practice, it is stated, not developed or justified. For example, no attempt is made to explain why four-electrode resistivity works where two-electrode surveys do not.
標簽： Field_Geophysics
上傳時間： 2020-06-09
上傳用戶：shancjb
Fun. We (your authors) wanted a word to describe our ultimate goal for this book, as well as a word we hope you (our reader) will use to describe it, and that’s the one we chose. There are others goals, of course, but in the end, when you’ve finished the book, we’re hoping you’ll have enjoyed the activities described in these pages. Many books use the Introduction to explain exactly what the book is about, what the reader will learn, what the reader needs (a skill or maybe an item or piece of software), and what the reader will be left with when that last page is completed. And this Introduction will do those things, but … hopefully it’ll make you excited to get started.
標簽： Adventures Arduino Station Escape Gemini from
上傳時間： 2020-06-09
上傳用戶：shancjb
This book was written by Michael Margolis with Nick Weldin to help you explore the amazing things you can do with Arduino. Arduino is a family of microcontrollers (tiny computers) and a software creation envi- ronment that makes it easy for you to create programs (called sketches) that can interact with the physical world. Things you make with Arduino can sense and respond to touch, sound, position, heat, and light. This type of technology, often referred to as physical computing, is used in all kinds of things, from the iPhone to automobile elec- tronics systems. Arduino makes it possible for anyone—even people with no program- ming or electronics experience—to use this rich and complex technology.
上傳時間： 2020-06-09
上傳用戶：shancjb
Have you ever looked at some gadget and wondered how it really worked? Maybe it was a remote control boat, the system that controls an elevator, a vending machine, or an electronic toy? Or have you wanted to create your own robot or electronic signals for a model railroad, or per- haps you’d like to capture and analyze weather data over time? Where and how do you start?
標簽： Introduction Workshop Hands-On Arduino
上傳時間： 2020-06-09
上傳用戶：shancjb
n recent years, there have been many books published on power system optimization. Most of these books do not cover applications of artifi cial intelligence based methods. Moreover, with the recent increase of artifi cial intelligence applications in various fi elds, it is becoming a new trend in solving optimization problems in engineering in general due to its advantages of being simple and effi cient in tackling complex problems. For this reason, the application of artifi cial intelligence in power systems has attracted the interest of many researchers around the world during the last two decades. This book is a result of our effort to provide information on the latest applications of artifi cial intelligence to optimization problems in power systems before and after deregulation.
標簽： Intelligence Artificial System Power in
上傳時間： 2020-06-10
上傳用戶：shancjb
The past decade has seen an explosion of machine learning research and appli- cations; especially, deep learning methods have enabled key advances in many applicationdomains,suchas computervision,speechprocessing,andgameplaying. However, the performance of many machine learning methods is very sensitive to a plethora of design decisions, which constitutes a considerable barrier for new users. This is particularly true in the booming field of deep learning, where human engineers need to select the right neural architectures, training procedures, regularization methods, and hyperparameters of all of these components in order to make their networks do what they are supposed to do with sufficient performance. This process has to be repeated for every application. Even experts are often left with tedious episodes of trial and error until they identify a good set of choices for a particular dataset.
標簽： Auto-Machine-Learning-Methods-Sys tems-Challenges
上傳時間： 2020-06-10
上傳用戶：shancjb
We’re living through exciting times. The landscape of what computers can do is changing by the week. Tasks that only a few years ago were thought to require higher cognition are getting solved by machines at near-superhuman levels of per- formance. Tasks such as describing a photographic image with a sentence in idiom- atic English, playing complex strategy game, and diagnosing a tumor from a radiological scan are all approachable now by a computer. Even more impressively, computers acquire the ability to solve such tasks through examples, rather than human-encoded of handcrafted rules.
標簽： Deep-Learning-with-PyTorch
上傳時間： 2020-06-10
上傳用戶：shancjb
Although state of the art in many typical machine learning tasks, deep learning algorithmsareverycostly interms ofenergyconsumption,duetotheirlargeamount of required computations and huge model sizes. Because of this, deep learning applications on battery-constrained wearables have only been possible through wireless connections with a resourceful cloud. This setup has several drawbacks. First, there are privacy concerns. Cloud computing requires users to share their raw data—images, video, locations, speech—with a remote system. Most users are not willing to do this. Second, the cloud-setup requires users to be connected all the time, which is unfeasible given current cellular coverage. Furthermore, real-time applications require low latency connections, which cannot be guaranteed using the current communication infrastructure. Finally, wireless connections are very inefficient—requiringtoo much energyper transferredbit for real-time data transfer on energy-constrained platforms.
標簽： Embedded_Deep_Learning Algorithms
上傳時間： 2020-06-10
上傳用戶：shancjb
Artificial Intelligence (AI) has undoubtedly been one of the most important buz- zwords over the past years. The goal in AI is to design algorithms that transform com- puters into “intelligent” agents. By intelligence here we do not necessarily mean an extraordinary level of smartness shown by superhuman; it rather often involves very basic problems that humans solve very frequently in their day-to-day life. This can be as simple as recognizing faces in an image, driving a car, playing a board game, or reading (and understanding) an article in a newspaper. The intelligent behaviour ex- hibited by humans when “reading” is one of the main goals for a subfield of AI called Natural Language Processing (NLP). Natural language 1 is one of the most complex tools used by humans for a wide range of reasons, for instance to communicate with others, to express thoughts, feelings and ideas, to ask questions, or to give instruc- tions. Therefore, it is crucial for computers to possess the ability to use the same tool in order to effectively interact with humans.
標簽： Embeddings Processing Language Natural in
上傳時間： 2020-06-10
上傳用戶：shancjb
Machinelearninghasgreatpotentialforimprovingproducts,processesandresearch.Butcomputers usually do not explain their predictions which is a barrier to the adoption of machine learning. This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model- agnosticmethodsforinterpretingblackboxmodelslikefeatureimportanceandaccumulatedlocal effects and explaining individual predictions with Shapley values and LIME.
標簽： interpretable-machine-learning
上傳時間： 2020-06-10
上傳用戶：shancjb
