Although the growth of longitudinal data archives is one of the most dramatic developments in the behavioural sciences, there has been a barrier to the effective use of these files due to a lack of understanding of the relation between research questions and archival data - until now. The authors of this volume illustrate how to use the model-fitting process to select and fit t...(展开全部)

Contemporary urban development is increasingly characterized by a reliance on diagrams to convey the rational, statistical point of view of the professional urban planner. In his new book "Urbanisms," architect Steven Holl suggests that just as modern medicine has recognized the power of the irrational psyche, urban planners need to realize that the experiential power of cities...(展开全部)

Book Description Do you want to be more successful at work? Do you want to improve your chances of promotion? Do you want to get on better with your colleagues? Daniel Goleman draws on unparalleled access to business leaders around the world and the thorough research that is his trademark. He demonstrates that emotional intelligence at work matters twice as much as cognitive a...(展开全部)

Book Description In his phenomenal bestseller, Emotional Intelligence, Daniel Goleman mapped the territory where IQ meets EQ, where we apply what we know to how we live. Spending over a year on the New York Times bestseller list, Emotional Intelligence provided the evidence for what many successful people already knew: being smart isn't just a matter of mastering facts; it's a ...(展开全部)

Do you have what it takes to succeed in your career? The secret of success is not what they taught you in school. What matters most is not IQ, not a business school degree, not even technical know-how or years of expertise. The single most important factor in job performance and advancement is emotional intelligence. Emotional intelligence is actually a set of skills that a...(展开全部)

This book is for architects and senior managers who are responsible for building a strategy around their current data architecture, helping them identify the need for a Data Lake implementation in an enterprise context. The reader will need a good knowledge of master data management and information lifecycle management, and experience of Big Data technologies.

This book is for architects and senior managers who are responsible for building a strategy around their current data architecture, helping them identify the need for a Data Lake implementation in an enterprise context. The reader will need a good knowledge of master data management and information lifecycle management, and experience of Big Data technologies.

Get more out of your legacy systems: more performance, functionality, reliability, and manageability Is your code easy to change? Can you get nearly instantaneous feedback when you do change it? Do you understand it? If the answer to any of these questions is no, you have legacy code, and it is draining time and money away from your development efforts. In this book, Mic...(展开全部)

Data Science with Python begins by introducing you to data science and teaches you to install the packages you need to create a data science coding environment. You will learn three major techniques in machine learning: unsupervised learning, supervised learning, and reinforcement learning. You will also explore basic classification and regression techniques, such as support vector machines, decision trees, and logistic regression.As you make your way through chapters, you will study the basic functions, data structures, and syntax of the Python language that are used to handle large datasets with ease. You will learn about NumPy and pandas libraries for matrix calculations and data manipulation, study how to use Matplotlib to create highly customizable visualizations, and apply the boosting algorithm XGBoost to make predictions. In the concluding chapters, you will explore convolutional neural networks (CNNs), deep learning algorithms used to predict what is in an image. You will also understand how to feed human sentences to a neural network, make the model process contextual information, and create human language processing systems to predict the outcome.By the end of this book, you will be able to understand and implement any new data science algorithm and have the confidence to experiment with tools or libraries other than those covered in the book.

Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects.Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you’re likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence.