Ruixin Zhang(张瑞昕）'s repositories
FIN-580-Advanced-Data-Science-and-Python-for-Finance-final-Project
Building a long-short strategy using self-made functions and backtest them via backtrader python modules
FIN-514-Final-Project--dispersion-trade
Used dispersion trade method and Vega-neutral strategy to construct a portfolio using GARCH and DCC models; measured the realized performance of the portfolio based on simulated VaR, Expected Shortfall and Greeks.
materials
Bonus materials, exercises, and example projects for our Python tutorials
FortunaGD
Data analysis projects in SQL, Python, R, Julia.
Coursera-UIUC-Applying-Data-Analytics-in-Finance
Course Description In this course, we will introduce a number of financial analytic techniques. You will learn why, when, and how to apply financial analytics in real-world situations. We will explore techniques to analyze time series data and how to evaluate the risk-reward trade off expounded in modern portfolio theory. While most of the focus will be on the prices, returns, and risks of corporate stocks, the analytical techniques can be leveraged in other domains. Finally, a short introduction to algorithmic trading concludes the course. After completing this course, you should be able to understand time series data, create forecasts, and determine the efficacy of the estimates. Also, you will be able to create a portfolio of assets using actual stock price data while optimizing risk and reward. Understanding financial data is an important skill as an analyst, manager, or consultant. Course Goals and Objectives Upon completion of this course, you should be able to: Understand the forecasting process. Evaluate a forecast. Describe time series data. Perform moving average analysis. Perform exponential smoothing. Develop a Holt-Winters model. Develop an ARIMA model. Understand how to create a portfolio of assets. Understand a basic trading algorithm.
python-for-finance
some useful machine learning tools applied in the financial field
Network-Analysis-in-Python
I'll try to consolidate everything you've learned through an in-depth case study of GitHub collaborator network data. This is a great example of real-world social network data, and your newly acquired skills will be fully tested. By the end of this chapter, you'll have developed your very own recommendation system to connect GitHub users who should collaborate together.
-A-Case-Study-in-Bokeh
I'll try to build a more sophisticated Bokeh data exploration application from the ground up based on the famous Gapminder dataset
OpenCourseCatalog
Bilibili 公开课目录
machine-learning-self-learning-code
I am learning machine learning all by myself. And I really want to record every machine-learning algorithm I have learned by uploading my self-made python code for each algorithm. Hopefully I can enjoy myself through the study and help myself achieve the goal of becoming a great data scientist!
wtfpython
A collection of surprising Python snippets and lesser-known features.
Virgilio
Your new Mentor for Data Science E-Learning.
awesome-python
A curated list of awesome Python frameworks, libraries, software and resources
awesome-deep-learning
A curated list of awesome Deep Learning tutorials, projects and communities.
OmniNet
Official Pytorch implementation of "OmniNet: A unified architecture for multi-modal multi-task learning" | Authors: Subhojeet Pramanik, Priyanka Agrawal, Aman Hussain
Algorithm_Interview_Notes-Chinese
2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记
120-Data-Science-Interview-Questions
Answers to 120 commonly asked data science interview questions.
courses-intro-to-unix-shell
Introduction to Shell for Data Science by Greg Wilson
course-nlp
A Code-First Introduction to NLP course
imbalanced-learn
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
statistical-thinking-in-python
The crucial last step of a data analysis pipeline hinges on the principles of statistical inference. With the power of Python-based tools, I can rapidly get up to speed and begin thinking statistically so that I can draw clear, succinct conclusions from the data I have acquired.
learn-python3
Learn Python 3 Sample Code
Web-Scraping-With-Python
I am new to data science. But I am really skillful in writing Python Codes. This time, I try to use limited python libraries to scrape news/information from multiple financial news websites. Please Enjoy!
numpy-ml
Machine learning, in numpy
algorithm-visualizer
:fireworks:Interactive Online Platform that Visualizes Algorithms from Code
DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
MEDIUM_NoteBook
Repository containing notebooks of my posts on Medium
learnopencv
Learn OpenCV : C++ and Python Examples
wtfpython-cn
wtfpython的中文翻译/施工结束/ 能力有限，欢迎帮我改进翻译