2021年中国品牌价值500强-Brand Finance

Personal Finances Pro 中文特别版是一款非常适合个人使用的而且非常容易使用功能强大的智能个人理财记账工具，它可以帮助你控制您的金钱，它将帮助您停止浪费和开始存您的金钱,能够有效地帮助您管理日常的开支和收入! 个人理财记账工具 Alzex Personal Finance Pro 中文版个人理财记账工具 Alzex Personal Finance Pro 中文版 Alzex Personal Finance Pro 特点 该软件允许你创建年度预算评估，跟踪收入和花费，并且计算你的净值。提供包括分类和各种不同收入水平的概要预算描述。 早年预算可以被导入到当前年度。包括用于分期偿还借贷，比较利息率，以及创建储蓄计划的计算器。储蓄计算器可以执行采用一次付清合计和年金计算的退休收入预测。概要浏览通过表格和图表对比每月和年度投资预算和实际收入和费用。 定制你自己的账户，事务类型和分类。事务可以使用年度和月度图表进行浏览，并且可以按照账户和分类进行过滤。 这些可以按照日期，账户，分类和总计进行排序。可以生成分解和重复事务。收入可以以月度为基础分配到各种不同的分类以及一个将被分配到各种不同存储目的的存储库当中。日期可以被保持和导出到 CSV (逗号分隔)或者文本文件当中。密码保护数据库可以保持你的私人记录的安全性。 Alzex Personal Finance Pro 使用方法 Personal Finances Pro是一个直观，易于使用的个人财务管理软件。从其他应用程序不同，它提供了一个非常漂亮的和深思熟虑的界面，易于使用，清晰的表述结果。该方案可以帮助您控制您的财务状况，了解你的钱哪里去，找准领域的过度开支，削减不必要的开支。 程序只需要很少的时间跟踪开支。这是很容易，适合初学者学习，并为电力用户提供了一套丰富的功能。 您可以在安装程序的usb驱动器上，它总是在手。您可以使用任何一台电脑上的程序，在家里，在办公室，还是在移动（即使禁止软件安装由系统管理员） 。所有数据都存储在USB驱动器和一台电脑上留下任何痕迹。 该计划背后的想法是按类别划分费用（收入） 。它可以让你看到多少钱，花了，但分析报告。类别是树形，每个类别可能有可能有自己的子类的子类。费用（收入）除以家庭成员和定义标签。所以，你可以很容易地看到从大局下来的资金流动到最小细节。

Python-for-Finance-Cookbook-master 代码

CFA一级试题 十一Corporate Finance Corporate Investing and Financing Decisions_removed

业财一体

the future of fintech future - integrating finance and technology in financial

Mathematics for Finance An introduction to Financial Engineering Second Edition Springer

适合从事金融量化工作的初级程序员学习

金融应用

Machine Learning for Finance: Principles and practice for financial insiders Author: Jannes Klaas Pub Date: 2019 ISBN: 978-1789136364 Pages: 456 Language: English Format: EPUB A guide to advances in machine learning for financial professionals, with working Python code 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. What you will learn Apply machine learning to structured data, natural language, photographs, and written text How machine learning can detect fraud, forecast financial trends, analyze customer sentiments, and more Implement heuristic baselines, time series, generative models, and reinforcement learning in Python, scikit-learn, Keras, and TensorFlow Dig deep into neural networks, examine uses of GANs and reinforcement learning Debug machine learning applications and prepare them for launch Address bias and privacy concerns in machine learning