Learn How to Apply Artificial Intelligence in Business
Over the years, machines have attained intelligence capabilities that were only known to man before. Self-driving cars and virtual assistants like Siri and Alexa are some of the examples of artificial intelligence in action in daily life.
For a business, artificial intelligence is important in increasing productivity, enhancing decision making and increasing profits. This book puts into perspective how artificial intelligence affects business.
With 14 comprehensive chapters, this book is the most detailed guide you will find on the internet on artificial intelligence for business.
Here is a rundown of what you learn:
How to get started with AI in your business
What benefits and impacts the use of AI will have in your business
How you can build and incorporate an AI strategy in your business
How machine learning and AI will enhance the competitiveness of your business
The best uses for AI in your business
The future of AI, especially for businesses
FAQ
Q: Who is this book suitable for?
A: This book is for business executives and students of business that want to be future proof. It will take you through the concepts of machine learning, artificial intelligence and deep learning and how you can use them to impact your business.
Q: At the end of this book, will I be able to implement AI in my business?
A: Yes. This book provides a step-by-step method on how you can develop machine learning and artificial intelligence projects for your business. Everything is covered: from developing a strategy to operationalizing ML and AI projects.
Grab your copy of this comprehensive guide to artificial intelligence for business and stand the test of time
Описание: A common feature of many approaches to modeling sensory statistics is an emphasis on capturing the ""average."" From early representations in the brain, to highly abstracted class categories in machine learning for classification tasks, central-tendency models based on the Gaussian distribution are a seemingly natural and obvious choice for modeling sensory data. However, insights from neuroscience, psychology, and computer vision suggest an alternate strategy: preferentially focusing representational resources on the extremes of the distribution of sensory inputs. The notion of treating extrema near a decision boundary as features is not necessarily new, but a comprehensive statistical theory of recognition based on extrema is only now just emerging in the computer vision literature. This book begins by introducing the statistical Extreme Value Theory (EVT) for visual recognition. In contrast to central-tendency modeling, it is hypothesized that distributions near decision boundaries form a more powerful model for recognition tasks by focusing coding resources on data that are arguably the most diagnostic features. EVT has several important properties: strong statistical grounding, better modeling accuracy near decision boundaries than Gaussian modeling, the ability to model asymmetric decision boundaries, and accurate prediction of the probability of an event beyond our experience. The second part of the book uses the theory to describe a new class of machine learning algorithms for decision making that are a measurable advance beyond the state-of-the-art. This includes methods for post-recognition score analysis, information fusion, multi-attribute spaces, and calibration of supervised machine learning algorithms.
Автор: Anandakumar Haldorai, Arulmurugan Ramu Название: Big Data Analytics for Sustainable Computing ISBN: 1522597506 ISBN-13(EAN): 9781522597506 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 32987.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science.
Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.
Автор: Anandakumar Haldorai, Arulmurugan Ramu Название: Big Data Analytics for Sustainable Computing ISBN: 1522597514 ISBN-13(EAN): 9781522597513 Издательство: Mare Nostrum (Eurospan) Цена: 27027.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.
Описание: Presents research exploring the theoretical and practical aspects of critical technological solutions within the farming industry. The book features coverage on a broad range of topics, including crop monitoring, precision livestock farming, and agronomic data processing.
Описание: As technology continues to saturate modern society, agriculture has started to adopt digital computing and data-driven innovations. This emergence of ""smart"" farming has led to various advancements in the field, including autonomous equipment and the collection of climate, livestock, and plant data. As connectivity and data management continue to revolutionize the farming industry, empirical research is a necessity for understanding these technological developments. Artificial Intelligence and IoT-Based Technologies for Sustainable Farming and Smart Agriculture provides emerging research exploring the theoretical and practical aspects of critical technological solutions within the farming industry. Featuring coverage on a broad range of topics such as crop monitoring, precision livestock farming, and agronomic data processing, this book is ideally designed for farmers, agriculturalists, product managers, farm holders, manufacturers, equipment suppliers, industrialists, governmental professionals, researchers, academicians, and students seeking current research on technological applications within agriculture and farming.
Описание: This book highlights the latest advances in the field of artificial intelligence and related technologies, with a special focus on sustainable development and environmentally friendly artificial intelligence applications.
Автор: Awasthi Shashank, Travieso-Gonzбlez Carlos M., Sanyal Goutam Название: Artificial Intelligence for a Sustainable Industry 4.0 ISBN: 3030770699 ISBN-13(EAN): 9783030770693 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Section 2 explores the sustainable engineering solutions development using AI, which addresses challenges in various computing techniques and opportunities in engineering design for sustainable development using IoT/AI and smart cities.
Описание: Do you want to understand machine learning? How it works and how is correlated to artificial intelligence and deep learning? If yes, then keep reading...
Machine Learning is based on mathematics, specifically statistics. It is a probabilistic discipline that began in the 1950s. Despite initial enthusiasm, research and development in Machine Learning languished for over 30 years, suffering from twin ills of a lack of data to work with and computers that were too slow to effectively work with what data they had.
It is no accident Machine Learning is coming into its own over the last 10 years. Until we began creating and storing massive amounts of data about our world, ML was mostly an idea in the minds of statisticians. And until computers reached a level of speed and power where these massive data sets could be ingested in a reasonable amount of time, the revolution couldn't happen. But as we digitize information about our world and ourselves, and computers continue to increase in speed and capacity exponentially, the ability for Machine Learning to learn from our data grows in depth and accuracy. Looking to the future, we can see only more and more data collection about our world, faster computer chips, and data transfer, and more avenues for ML to develop in, to grow and learn, and to serve humanity.
When most people think of machine learning, they either have no idea what it is, or they automatically think about artificial intelligence in the form of a robotic species that rivals humans. While these fascinating subspecies may one day exist as the result of machine learning developments, right now the primary focus is on how machine learning programs can become excellent at very specific tasks. Most machine learning technology is developed in such a way that it is excellent at performing one or, at most, two tasks. By focusing entire technology on one single task, they can ensure that it runs that task perfectly, and that it does not get confused between the tasks that it is trying to accomplish. While simple computing software like the one that runs your computer can easily run multiple programs at once with little chance of crashing, the technology that is used to run machine learning technology is far more complex. As researchers study it, they strive to keep the algorithms mostly separate, or specifically focused on completing just one goal, on minimizing room for error.
It is likely that as we become more familiar with machine learning technology and more educated in the algorithms, we will start to see more and more machines completing multiple tasks, rather than just one. At this point, that is the long-term goal for many scientists who want to see these machines becoming more efficient, and requiring less hardware. After all, the hardware used to run some of these machines is not always the greenest technology, so the fewer hardware casings that technology needs to be stored in, the less of a footprint the technology sector will have on the planet. This book aims to educate you on the truth about machine learning.
This book gives a comprehensive guide on the following:
If your dream is to become a Python pro, or you always want to code like a boss, solve real-world problems, build web apps, or even automate repetitive tasks, then you've come to the right place.
By the end of this book, you will have mastered the fundamentals of Python language. You will learn how to create programs that will save you time and simplify your life.
Python is a straightforward language, so even if this is your first time to learn any programming language, you can learn Python without experiencing any issues.
Python has multiple applications, and so you've got a high probability of getting a great job once you become a pro in Python language.
Whether it's in web development, data analysis, scripting, and machine learning, all require that you be experienced in Python.
This is a beginner guide that will take you from absolute scratch to creating your first Python program.
Not only that, but you'll also learn lots of stuff about the Django Python framework.
With Django, you will learn how to create web apps very quickly and efficiently.
Here are some of the things you will learn:
How to install Python
How to install virtual environment
How to install Django
How to create a Django app
How to run Django commands
How to define and use functions
What are variables and how to use them
And many more topics
Python is hot right now.
It has a high demand in the IT sector.
Python skills keep growing and growing.
If you want to get into programming as a career, upgrade your existing job, or open up new opportunities in the IT field, you need to start learning Python today.
And what a better way to kick start your career in Python with this easy to read step by step guide.
Автор: Paula Boddington Название: Towards a Code of Ethics for Artificial Intelligence ISBN: 3319869051 ISBN-13(EAN): 9783319869056 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Поставка под заказ.
Описание: People use science every single day in their jobs! From a smoothie maker creating a vortex to blend fruit and vegetables to firefighters extinguishing a blaze by breaking the fire triangle, the jobs and occupations at the heart of this super-creative non-fiction read will inspire all children to seek out the everyday science in the world around us.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
