Regular price: $19.95
Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.
An introduction for everyone. Rather than a "how to" for hands-on techies, this book - now in its revised and updated edition - serves lay listeners and experts alike by covering new case studies and the latest state-of-the-art techniques. In this rich, fascinating, and surprisingly accessible introduction, leading expert Eric Siegel reveals how predictive analytics works and how it affects everyone every day.
The need for precise, actionable, real-time Business Intelligence (BI) lies at the heart of the role of Big Data in modern commerce. In turn, the art of Data Science lies at the nexus of Big Data and BI, providing the essential methods by which BI can be extracted from Big Data's great black mass of constantly flowing, unstructured information. This combination has a created a new profession: an elite and specialized class of highly-compensated professionals specially skilled at data cleaning, analysis, and visualization.
Oxford professor and author Viktor Mayer-Schönberger joins Economist data editor and commentator Kenneth Cukier to deliver insight into the hottest trend in technology. "Big data" makes it possible to instantly analyze and draw conclusions from vast stores of information, enabling revolutionary breakthroughs in business, health, politics, and education. But big data also raises troubling social and privacy concerns sure to be a major talking point in the years ahead.
Mathematical corporations - the organizations that will master the future - will outcompete high-flying rivals by merging the best of human ingenuity with machine intelligence. While smart machines are weapon number one for organizations, leaders are still the drivers of breakthroughs. Only they can ask crucial questions to capitalize on business opportunities newly discovered in oceans of data.
Data Analytics is a 7-book bundle, including topics like: Data Analytics for Beginners; Deep Learning with Keras; Analyzing Data with Power BI; and Reinforcement Learning, Artificial Intelligence, Text Analytics, and Convolutional Neural Networks with Python. You will start by putting data analytics to work, learning about the rise of data analytics and building the fundamentals to master algorithms and processes using Python.
Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.
An introduction for everyone. Rather than a "how to" for hands-on techies, this book - now in its revised and updated edition - serves lay listeners and experts alike by covering new case studies and the latest state-of-the-art techniques. In this rich, fascinating, and surprisingly accessible introduction, leading expert Eric Siegel reveals how predictive analytics works and how it affects everyone every day.
The need for precise, actionable, real-time Business Intelligence (BI) lies at the heart of the role of Big Data in modern commerce. In turn, the art of Data Science lies at the nexus of Big Data and BI, providing the essential methods by which BI can be extracted from Big Data's great black mass of constantly flowing, unstructured information. This combination has a created a new profession: an elite and specialized class of highly-compensated professionals specially skilled at data cleaning, analysis, and visualization.
Oxford professor and author Viktor Mayer-Schönberger joins Economist data editor and commentator Kenneth Cukier to deliver insight into the hottest trend in technology. "Big data" makes it possible to instantly analyze and draw conclusions from vast stores of information, enabling revolutionary breakthroughs in business, health, politics, and education. But big data also raises troubling social and privacy concerns sure to be a major talking point in the years ahead.
Mathematical corporations - the organizations that will master the future - will outcompete high-flying rivals by merging the best of human ingenuity with machine intelligence. While smart machines are weapon number one for organizations, leaders are still the drivers of breakthroughs. Only they can ask crucial questions to capitalize on business opportunities newly discovered in oceans of data.
Data Analytics is a 7-book bundle, including topics like: Data Analytics for Beginners; Deep Learning with Keras; Analyzing Data with Power BI; and Reinforcement Learning, Artificial Intelligence, Text Analytics, and Convolutional Neural Networks with Python. You will start by putting data analytics to work, learning about the rise of data analytics and building the fundamentals to master algorithms and processes using Python.
Facebook, PayPal, Alibaba, Uber - these seemingly disparate companies have upended entire industries by harnessing a single phenomenon: the platform business model. Platform Revolution delivers the first comprehensive analysis of how platforms use technology to match producers and consumers in a multisided marketplace, unlocking hidden resources and creating new forms of value. When a company like Uber connects drivers with passengers, everybody wins - except traditional cab companies, which are scrambling to survive.
From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you'll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.
Get smart - learn to convert the promise of Big Data into real-world results. There is so much buzz around big data. We all need to know what it is and how it works. But what will set you apart from the rest is actually knowing how to use big data to get solid, real-world business results - and putting that in place to improve performance. Big Data shows you how to implement the same practices that leading firms have used to access new dimensions of profitability.
Leading innovation expert Alec Ross explains what's next for the world, mapping out the advances and stumbling blocks that will emerge in the next 10 years - for businesses, governments, and the global community - and how we can navigate them.
Lars Nielsen and Noreen Burlingame provide a brief, understandable, user-friendly guide to all aspects of Data Science. The authors address the various skills required, the key steps in the Data Science process, software technology related to the effective practice of Data Science, and the best rising academic programs for training in the field.
The Internet and smartphone are just the latest in a 250-year-long cycle of disruption that has continuously changed the way we live, the way we work, and the way we interact. The coming Augmented Age, however, promises a level of disruption, behavioral shifts, and changes that are unparalleled. While consumers today are camping outside of an Apple store waiting to be one of the first to score a new Apple Watch or iPhone, the next generation of wearables will be able to predict if we're likely to have a heart attack and recommend a course of action.
Taking up where the best-selling A Simple Introduction to Data Science, left off, Lars Nielsen's A Simple Introduction to Data Science, Book 2 expands on elementary concepts introduced in the first volume while at the same time embracing several new and key topics.
All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such problems for decades.
Are you ready to learn how to understand smart big data, data mining, and data analytics for improved business performance, life decisions, and more? If so, you've come to the right place - regardless of how little experience you may have!
This is a two book bundle related to data analytics and learning Python programming from scratch!
Martin Lindstrom, a modern-day Sherlock Holmes, harnesses the power of "small data" in his quest to discover the next big thing. Hired by the world's leading brands to find out what makes their customers tick, Martin Lindstrom spends 300 nights a year in strangers' homes, carefully observing every detail in order to uncover their hidden desires and, ultimately, the clues to a multimillion-dollar product.
No skill is more important in today's world than being able to think about, understand, and act on information in an effective and responsible way. What's more, at no point in human history have we had access to so much information, with such relative ease, as we do in the 21st century. But because misinformation out there has increased as well, critical thinking is more important than ever. These 24 rewarding lectures equip you with the knowledge and techniques you need to become a savvier, sharper critical thinker in your professional and personal life.
#1 BESTSELLER This book is a scientific expedition to research and explore the enterprise-grade big data appliances with blended OLTP and OLAP capabilities. Enterprise database systems with the aid of big data analytics create an intelligent ecosystem by taming and wrangling the data coming from extreme-disparate sources of structured and unstructured channels with massive parallelization techniques to discover, visualize, predict, and action the patterns and trends of mashups of big data. The book delves deeper into the research results of industry relevant case studies with the disruption of in-memory computing platform innovation that diffuses high-speed computing and dynamic performance for business applications and explores how these modern big data analytics tools shape the future of aerospace, automotive, consumer goods and beverages, healthcare, government services, high tech, and public sector industries.
What disappointed you about Big Data Appliances for In-Memory Computing?
Was hoping for more comparison of technologies... The book was more of an sap Hana fest, with the occasional anicdote about why technology x is less awesome than sap Hana.
What could Dr. Ganapathi Pulipaka have done to make this a more enjoyable book for you?
By not mechanically repeating the exact same evidence in multiple chapters.
How could the performance have been better?
Well...even though It is a technical book... There are compelling stories behind the facts. These compelling stories were treated mostly as lists of facts.
What reaction did this book spark in you? Anger, sadness, disappointment?
I felt like I paid to listen to a 5 hour sap commercial.
Any additional comments?
I am looking forward to the movie.
5 of 5 people found this review helpful
This has some decent information and might be ok as a reference guide, but it doesn't work well as an audio book. It seems almost like an SAP advertisement.
1 of 1 people found this review helpful
What did you love best about Big Data Appliances for In-Memory Computing?
A detailed explanation of the various concepts of Big Data and how the latest advancements in computing landscapes are changing the way Data is being used in various organizations to drive business success.Also a very effective guide to executives at various levels of an organization on how to handle Big Data Implementations and drive successful projects.
What was one of the most memorable moments of Big Data Appliances for In-Memory Computing?
Real world examples are given in the book which explained the before and after effects of implementing Big Data software in various organizations. These examples left a very good impression about the benefits of Big Data and we are eager to adopt these technologies in our organization as well.
Which character – as performed by Jodie Bentley – was your favorite?
This is the first book I listened by her
Was this a book you wanted to listen to all in one sitting?
Yes
1 of 1 people found this review helpful
What made the experience of listening to Big Data Appliances for In-Memory Computing the most enjoyable?
This audiobook is not for beginners, but the author of the book builds the momentum from starting the history to most advanced complex topics of in-memory computing. It is enjoyable.
What other book might you compare Big Data Appliances for In-Memory Computing to and why?
I don't know if there's any other audiobook with such high-quality or content.
Which scene was your favorite?
I liked all the chapters.
Was there a moment in the book that particularly moved you?
The future of in-memory computing.
Any additional comments?
Excellent book. Highly recommend it.
1 of 1 people found this review helpful
Would you recommend this audiobook to a friend? If so, why?
Absolutely !The laudable research study provided an intensive and comprehensive work such as establishing the problem, framework, research questions, literature review, and qualitative analysis
What did you like best about this story?
He compared and contrasted several analytics and statistics tools such as IBM DB2 Blu, Oracle Exadata, Tableau, etc. with interesting findings and lucid results from qualitative surveys, interviews in the credible resources such as IDC, SAP customers
Which scene was your favorite?
Dr. Pulipaka’s book presents a scholarly research guide for corporations or high-tech organizations to use SAP HANA (Systems, applications, and products – High-performance analytic appliance) for robustly elaborating their big data for meaningful information, holistic knowledge, and professional wisdom.
Did you have an extreme reaction to this book? Did it make you laugh or cry?
The fervid recommendation for SAP HANA, particularly in-memory flash is the great idea for future research.
Any additional comments?
I like to see more specific information of hardware (HW) and software (SW) on the SAP HANA platform such as:
- SW: system software, OS, supporting software, application software, OLAP, OLTP, RDBMS, etc.
- HW: Memory, computer type, microprocessors, server type, hosts, etc
Is SAP HANA packaged and portable from one system to another system?
Is any particular training required to use SAP HANA ?
Would you listen to Big Data Appliances for In-Memory Computing again? Why?
Yes. This book is largely interesting with heavy substance of big data, SAP HANA, IBM DB2 and Oracle. Exadata and more than dime a dozen big data tools, data visualization tools, business analytics, in -memory computing architecture and how the strategy of setting up data analytics center of excellence provide big value to the organizations.
What other book might you compare Big Data Appliances for In-Memory Computing to and why?
This is the first book I am encountering and hence would not be able to compare with anything.
What about Jodie Bentley’s performance did you like?
Deliverance to put it short.
Did you have an extreme reaction to this book? Did it make you laugh or cry?
Highly structured book written in APA 6th edition format that works as a dissertation and serves the corporations commercially to build their data analytics centers of excellence.
Any additional comments?
The book provides the past, present and the future of bigdata and in-memory computing with the aid of ground-breaking technology of DRAM memory and how the in-memory computing works with Apache Hadoop and R to process gargantuan volumes of big data.
What did you love best about Big Data Appliances for In-Memory Computing?
This book explains a details analysis on real world scenarios and solutions for data analytic problems. This book is good building blocks for my SAP HANA In-Memory Skills. I got lot of knowledge on Big data and its application in current market. Big data is really useful in analyzing huge amount of data in very less time and efficiently.
What other book might you compare Big Data Appliances for In-Memory Computing to and why?
When I searched for SAP Big Data, there is no other audio book available on this topic. Hence this is the first Audiobook ever released on SAP Big Data .
Which character – as performed by Jodie Bentley – was your favorite?
This is a non-fiction technology Big data book. There are no other characters in the book other than Big Data and SAP.
Was there a moment in the book that particularly moved you?
The topic on future of In-Memory computing was very impressive part in this book.
Any additional comments?
The book has bee thoroughly researched on Big Data and In-Memory Computing on SAP HANA.
If you could sum up Big Data Appliances for In-Memory Computing in three words, what would they be?
This audio book is exhilarating and provides deep insights into the big data and in-memory computing with a number of tools and strategies to set up a data center of excellence for advanced analytics, business analytics, and date warehousing of the organization.
What was one of the most memorable moments of Big Data Appliances for In-Memory Computing?
I liked all the chapter. Particularly, the author clearly provides the case studies in excess of some 60 or 70 in multiple industries.
Which character – as performed by Jodie Bentley – was your favorite?
Narrator.
Was there a moment in the book that particularly moved you?
The author conducts a thorough deep research on the topics with his experience.
Any additional comments?
Highly rated and Highly recommended. Top-notch quality.
Excellent content and presentation any layman can understand several Bigdata and in-memory business cases well explained with in depth texhnology secrets from roots to latest trends. I have read many audio books bur Jodi audio naration was excellnt and outstanding.
1 of 2 people found this review helpful
Bought this audiobook for knowledge in 'In memory computing' .
...but this is just marketing document for SAP HANA. Wasted time and money. Good only for person who is in profession for selling SAP HANA.