The recent financial crisis was an accident, a "perfect storm" fueled by an unforeseeable confluence of events that unfortunately combined to bring down the global financial systems. And policy makers? They did everything they could, given their limited authority. It was all a terrible, unavoidable accident. Or at least this is the story told and retold by a chorus of luminarie...(展开全部)

克里斯汀•麦金莱：美国畅销作家，音乐人，著名主持人，同时还是一名机械工程师，曾参与电力生产、工业技术以及商业建造等重大工程。

Financial data analysts and data scientists who want to use SAS to process and analyze financial data and find hidden patterns and trends from it will find this book useful. Prior exposure to SAS will be helpful but is not mandatory. Some basic understanding of the financial concepts is required.

Machine Learning for Finance explores new advances in machine learning and shows how they can be applied across the financial sector, including in insurance, transactions, and lending. It explains the concepts and algorithms behind the main machine learning techniques and provides example Python code for implementing the models yourself.The book is based on Jannes Klaas’ experience of running machine learning training courses for financial professionals. Rather than providing ready-made financial algorithms, the book focuses on the advanced ML concepts and ideas that can be applied in a wide variety of ways.The book shows how machine learning works on structured data, text, images, and time series. It includes coverage of generative adversarial learning, reinforcement learning, debugging, and launching machine learning products. It discusses how to fight bias in machine learning and ends with an exploration of Bayesian inference and probabilistic programming.

Machine Learning for Finance explores new advances in machine learning and shows how they can be applied across the financial sector, including in insurance, transactions, and lending. It explains the concepts and algorithms behind the main machine learning techniques and provides example Python code for implementing the models yourself.The book is based on Jannes Klaas’ experience of running machine learning training courses for financial professionals. Rather than providing ready-made financial algorithms, the book focuses on the advanced ML concepts and ideas that can be applied in a wide variety of ways.The book shows how machine learning works on structured data, text, images, and time series. It includes coverage of generative adversarial learning, reinforcement learning, debugging, and launching machine learning products. It discusses how to fight bias in machine learning and ends with an exploration of Bayesian inference and probabilistic programming.

The long-awaited follow-up to the New York Times bestseller Getting Things Done. David Allen’s Getting Things Done hit a nerve and ignited a movement with businesses, students, soccer moms, and techies all the way from Silicon Valley to Europe and Asia. Now, David Allen leads the world on a new path to achieve focus, control, and perspective. Throw out everything you know about...(展开全部)

What I notice is that people feel very comfortable coming up to me and talking. It's the greatest compliment in the world. They perceive that I'm user-friendly, approachable, and accessible, and they're absolutely correct," says Tim Gunn to The Boston Globe, and millions of armchair fashionistas couldn't agree more. Tim is adored by the masses-both Project Runway fans and non-w...(展开全部)

Yves Hilpsch是Python Quants（德国）股份有限公司的创始人和任事股东，也是Python Quants（纽约）有限责任公司的共同创办人。该集团提供基于Python的金融和衍生品分析软件（参见http://pythonquants.com，http://quant-platfrom.com和http://dx-analytics.com），以及和Python及金融相关的咨询、开发和培训服务。 Yves还是Derivatives Analytics with Python（Wiley Finance，2015）的作者。作为获得数理金融学博士学位的商业管理专业研究生，他在萨尔州大学讲授计算金融学中的数值化方法课程。

This book celebrates Michael Stonebraker's accomplishments that led to his 2014 ACM A.M. Turing Award "for fundamental contributions to the concepts and practices underlying modern database systems." The book describes, for the broad computing community, the unique nature, significance, and impact of Mike's achievements in advancing modern database systems over more than forty ...(展开全部)