In financial markets, two of the most common trading strategies used by investors are the momentum and mean reversion strategies. If a stock exhibits momentum…

Added by Marco Tavora on July 4, 2019 at 12:30am — 2 Comments

The covariance matrix has many interesting properties, and it can be found in mixture models, component analysis, Kalman filters, and more. Developing an intuition for how the covariance matrix operates is useful in understanding its practical implications. This article will focus on a few important properties, associated proofs, and then some interesting practical applications, i.e., extracting transformed polygons from a Gaussian mixture's covariance matrix.

I have often found that…

ContinueAdded by Rohan Kotwani on May 26, 2019 at 7:30am — No Comments

It is a well-known fact that neural networks can approximate the output of any continuous mathematical function, no matter how complicated it might be. Take for instance the function below:…

Added by Marco Tavora on May 1, 2019 at 4:52am — No Comments

As an academic discipline, the rate of maturation for data science should be measured in light years. Although it's really only about 10 years old as a field of study – with the first Ph.D. program in the country emerging just four years ago – most, major universities across the world have integrated data science into their portfolio of degree options. Universities…

ContinueAdded by Jennifer Lewis Priestley on February 12, 2019 at 10:52am — No Comments

Imagine that one day, you see people are queuing up in front of **Bank A**; so you ask the staff at the counter, you are told that they are offering anyone (regardless of their credit history) a loan of $100,000 at a fixed annual rate at **2%**. You then look around, the **Bank B** next door offers 1-year term deposit with a fixed annual rate at **3%** for the same amount ($100,000). After 5 minutes' waiting, you sign for the loan from Bank…

Added by Zhongmin Luo on November 21, 2018 at 2:30pm — 2 Comments

I am halfway through my journey of being enough Mathematically literate to understand and work comfortably with Data Science books, posts, articles and journals. I wrote about my learning sabbatical earlier here. Before I go on I want to reiterate few things which have established my way of learning and working. Whenever I want to learn…

Continue- How the Mathematics of Fractals Can Help Predict Stock Markets Shifts
- Create Transformed, N-Dimensional Polygons with Covariance Matrix
- The Approximation Power of Neural Networks (with Python codes)
- Maslow's Hierarchy of Data Science: Why Math and Science Still Matter
- An Application of Data Science and Mathematics in Finance
- Learning Mathematics for Data Science

- How the Mathematics of Fractals Can Help Predict Stock Markets Shifts
- Maslow's Hierarchy of Data Science: Why Math and Science Still Matter
- Create Transformed, N-Dimensional Polygons with Covariance Matrix
- Learning Mathematics for Data Science
- The Approximation Power of Neural Networks (with Python codes)
- An Application of Data Science and Mathematics in Finance

**2020**

**2019**

- December (112)
- November (125)
- October (123)
- September (109)
- August (96)
- July (123)
- June (122)
- May (137)
- April (120)
- March (122)
- February (111)
- January (116)

**2018**

- December (109)
- November (108)
- October (114)
- September (116)
- August (120)
- July (110)
- June (132)
- May (135)
- April (118)
- March (137)
- February (134)
- January (132)

**2017**

- December (110)
- November (152)
- October (199)
- September (152)
- August (234)
- July (159)
- June (186)
- May (165)
- April (175)
- March (207)
- February (152)
- January (168)

**2016**

- December (129)
- November (164)
- October (157)
- September (174)
- August (170)
- July (137)
- June (225)
- May (177)
- April (170)
- March (200)
- February (182)
- January (198)

**2015**

- December (231)
- November (295)
- October (245)
- September (239)
- August (178)
- July (154)
- June (154)
- May (143)
- April (168)
- March (126)
- February (134)
- January (128)

**2014**

- December (104)
- November (113)
- October (141)
- September (129)
- August (101)
- July (104)
- June (91)
- May (120)
- April (86)
- March (117)
- February (99)
- January (112)

**2013**

- December (90)
- November (93)
- October (113)
- September (83)
- August (77)
- July (68)
- June (57)
- May (59)
- April (44)
- March (51)
- February (41)
- January (61)

**2012**

- December (39)
- November (65)
- October (73)
- September (44)
- August (23)
- July (20)
- June (22)
- May (51)
- April (40)
- March (26)
- February (37)
- January (18)

**2011**

- December (58)

**1999**

- November (3)

© 2020 Data Science Central ® Powered by

Badges | Report an Issue | Privacy Policy | Terms of Service

**Most Popular Content on DSC**

To not miss this type of content in the future, subscribe to our newsletter.

- Book: Statistics -- New Foundations, Toolbox, and Machine Learning Recipes
- Book: Classification and Regression In a Weekend - With Python
- Book: Applied Stochastic Processes
- Long-range Correlations in Time Series: Modeling, Testing, Case Study
- How to Automatically Determine the Number of Clusters in your Data
- New Machine Learning Cheat Sheet | Old one
- Confidence Intervals Without Pain - With Resampling
- Advanced Machine Learning with Basic Excel
- New Perspectives on Statistical Distributions and Deep Learning
- Fascinating New Results in the Theory of Randomness
- Fast Combinatorial Feature Selection

**Other popular resources**

- Comprehensive Repository of Data Science and ML Resources
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- 100 Data Science Interview Questions and Answers
- Cheat Sheets | Curated Articles | Search | Jobs | Courses
- Post a Blog | Forum Questions | Books | Salaries | News

**Archives:** 2008-2014 |
2015-2016 |
2017-2019 |
Book 1 |
Book 2 |
More

**Most popular articles**

- Free Book and Resources for DSC Members
- New Perspectives on Statistical Distributions and Deep Learning
- Time series, Growth Modeling and Data Science Wizardy
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- Comprehensive Repository of Data Science and ML Resources
- Advanced Machine Learning with Basic Excel
- Difference between ML, Data Science, AI, Deep Learning, and Statistics
- Selected Business Analytics, Data Science and ML articles
- How to Automatically Determine the Number of Clusters in your Data
- Fascinating New Results in the Theory of Randomness
- Hire a Data Scientist | Search DSC | Find a Job
- Post a Blog | Forum Questions