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Progress in Medicinal Chemistry provides a review of eclectic developments in medicinal chemistry. This volume continues in the serial's tradition of providing an insight into the skills required of the modern medicinal chemist; in particular, the use of an appropriate selection of the wide range of tools now available to solve key scientific problems. - Presents the latest research in the field of drug discovery - Publishes on a twice yearly basis to bring you the most innovative updates in medicinal chemistry - Available as an online resource via ScienceDirect
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why ...
This CD-ROM and textbook package introduces chemistry students to the world of molecular orbitals using 3D and VRML representations. An overview of the basic chemistry and physics needed enables readers to move quickly onto the CD. The CD-ROM itself contains an extended interactive textbook and a broad selection of classical organic compounds and inorganic complex ligands complete with their orbitals. Moreover, interactive demonstrations allow students to alter relevant parameters and watch the change in the orbitals'characteristics or take a walk through this fascinating 3D world.
Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both e...
As tech products become more prevalent today, the demand for machine learning professionals continues to grow. But the responsibilities and skill sets required of ML professionals still vary drastically from company to company, making the interview process difficult to predict. In this guide, data science leader Susan Shu Chang shows you how to tackle the ML hiring process. Having served as principal data scientist in several companies, Chang has considerable experience as both ML interviewer and interviewee. She'll take you through the highly selective recruitment process by sharing hard-won lessons she learned along the way. You'll quickly understand how to successfully navigate your way t...
Starting a new career in data analytics? Excel 2023: Manage Your New Career in Data Analytics with Dr Vinod Walwante - डॉ. विनोद वाळवंटे is the resource to help you develop the necessary Excel skills. This book focuses on practical, real-world applications of Excel 2023, guiding you through key tasks in data analysis. Whether you're just beginning in data analytics or looking to improve your skills, Dr Vinod Walwante - डॉ. विनोद वाळवंटे offers clear instructions and hands-on exercises. Discover how to work with large datasets, create effective reports, and use advanced Excel functions to tackle complex problems. The book covers a wide r...
Practical Time Series Forecasting with R: A Hands-On Guide, Third Edition provides an applied approach to time-series forecasting. Forecasting is an essential component of predictive analytics. The book introduces popular forecasting methods and approaches used in a variety of business applications. The book offers clear explanations, practical examples, and end-of-chapter exercises and cases. Readers will learn to use forecasting methods using the free open-source R software to develop effective forecasting solutions that extract business value from time series data. This edition features the R fable package, full color, enhanced organization, and new material. It includes: - Popular foreca...
Most of the high-profile cases of real or perceived unethical activity in data science arenâ??t matters of bad intent. Rather, they occur because the ethics simply arenâ??t thought through well enough. Being ethical takes constant diligence, and in many situations identifying the right choice can be difficult. In this in-depth book, contributors from top companies in technology, finance, and other industries share experiences and lessons learned from collecting, managing, and analyzing data ethically. Data science professionals, managers, and tech leaders will gain a better understanding of ethics through powerful, real-world best practices. Articles include: Ethics Is Not a Binary Concept...
Artificial Intelligence for Capital Market throws light on the application of AI/ML techniques in the financial capital markets. This book discusses the challenges posed by the AI/ML techniques as these are prone to "black box" syndrome. The complexity of understanding the underlying dynamics for results generated by these methods is one of the major concerns which is highlighted in this book. Features: Showcases artificial intelligence in finance service industry Explains credit and risk analysis Elaborates on cryptocurrencies and blockchain technology Focuses on the optimal choice of asset pricing model Introduces testing of market efficiency and forecasting in the Indian stock market This book serves as a reference book for academicians, industry professionals, traders, finance managers and stock brokers. It may also be used as textbook for graduate level courses in financial services and financial analytics.