A Data Science Central Community
This list of lists contains books, notebooks, presentations, cheat sheets, and tutorials covering all aspects of data science, machine learning, deep learning, statistics, math, and more, with most documents featuring Python or R code and numerous illustrations or case studies. All this material is available for free, and consists of content mostly created in 2019 and 2018, by various top experts in their respective fields. A few of these documents are available on LinkedIn: see last…Continue
Added by Vincent Granville on October 13, 2019 at 11:00am — No Comments
I have used synthetic data sets many times for simulation purposes, most recently in my articles Six degrees of Separations between any two Datasets and How to Lie with p-values. Many…Continue
Added by Vincent Granville on October 2, 2019 at 5:00pm — No Comments
This is an interesting data science conjecture, inspired by the well known six degrees of separation problem, stating that there is a link involving no more than 6 connections between any two people on Earth, say between you and anyone living (say) in North Korea.
Here the link is between any two univariate data sets…Continue
Added by Vincent Granville on September 9, 2019 at 10:30am — No Comments
The material discussed here is also of interest to machine learning, AI, big data, and data science practitioners, as much of the work is based on heavy data processing, algorithms, efficient coding, testing, and experimentation. Also, it's not just two new conjectures, but paths and suggestions to solve these problems. The last section contains a few new, original exercises, some with solutions, and may be useful to students, researchers, and instructors offering math and statistics classes…Continue
Added by Vincent Granville on September 8, 2019 at 4:09am — No Comments
Being extremely versatile general purpose, professional programming language, Python offers plenty of applications. Python language is user-friendly and simple to grasp and this made it popular throughout the world. Python plays a critical role for data scientists to find out lucrative job opportunities.
Today, Python has become the most in-demand programming language in the data science world. Python offers an extensive range…Continue
Added by Divyesh Aegis on September 5, 2019 at 12:00am — No Comments
Machine learning is a hot topic in research and industry, with new methodologies developed all the time. The speed and complexity of the field makes keeping up with new techniques difficult even for experts — and potentially overwhelming for beginners.
To demystify machine learning and to offer a learning path for those who are new to the core…Continue
Added by Vincent Granville on August 30, 2019 at 11:08am — No Comments
I introduce here a family of very peculiar statistical distributions governed by two parameters: p, a real number in [0, 1], and b, an integer > 1.
Potential applications are found in cryptography, Fintech (stock market modeling), Bitcoin, number theory, random number…Continue
Added by Vincent Granville on August 30, 2019 at 10:11am — No Comments
Continued fractions are usually considered as a beautiful, curious mathematical topic, but with applications mostly theoretical and limited to math and number theory. Here we show how it can be used in applied business and economics contexts, leveraging the mathematical theory developed for continued fraction, to model and explain natural phenomena. …Continue
Added by Vincent Granville on August 30, 2019 at 9:42am — No Comments
In the data-driven enterprise system, Spark has become a popular name that is easy to use, offer speed and versatility. The data can be understood at fast speed allowing one to make faster decisions. The Big Data has a huge benefit with the faster data processing of Spark. This clustering of large datasets works with a framework in open source that helps in analyzing. The codes are done in the Scala that has made it possible and easier for data processing that gives a certain boost to the…Continue
Added by Divyesh Aegis on August 13, 2019 at 12:51am — No Comments
In my previous posts, I compared model evaluation techniques using Statistical Tools & Tests and commonly used Classification and Clustering evaluation techniques
In this post, I'll take a look at how you can compare regression models. Comparing regression models is perhaps one of the trickiest tasks to complete in the "comparing models" arena; The reason is that there are literally dozens of statistics you can calculate to compare regression models, including:
Added by Vincent Granville on August 8, 2019 at 10:37am — No Comments
A brief explanation is:
Added by Vincent Granville on August 8, 2019 at 10:29am — No Comments
Decision Trees, Random Forests and Boosting are among the top 16 data science and machine learning tools used by data scientists. The three methods are similar, with a significant amount of overlap. In a nutshell:
Added by Vincent Granville on August 8, 2019 at 10:25am — No Comments
Properly implemented Machine Learning (ML) models can have a positive effect on organizational efficiency. It is first necessary to understand how these models are created, how they function, and how they are put into production.
The Definition of a Machine Learning Model
When a computer is presented with questions within a particular domain, a machine learning model will run an algorithm that will enable it to resolve those questions. These algorithms are not…Continue
Added by Arash Aghlara on August 7, 2019 at 3:30am — No Comments
Python is an extremely popular programming language. It is not just apt for generic purposes but it is extremely easy to read and use as well. The main reason why Python is used by a majority of people these days is the fact that it allows the programmers to save their time by using only limited lines of codes. In order to accomplish tasks, the developers do not have to spend a lot of time on coding, unlike the other languages. Rather, all they can do is, spend time on…Continue
Added by Divyesh Aegis on July 25, 2019 at 12:53am — No Comments
Python was introduced in 1991 by Guido Van Rossum as a high level, general purpose language. Even today, it supports multiple programming paradigms including procedural, object oriented and functional. Soon, it became one of the most popular languages in the industry, and in fact is the very language that influence Ruby and Swift. Even TIOBE Index reports mentions python as the third most popular…Continue
Added by Divyesh Aegis on July 16, 2019 at 12:55am — No Comments
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 (or trending behavior as shown in the figure below), its price on the current period is more likely to increase (decrease) if it has already increased (decreased) on the previous period.
When the return of a stock at time t depends in some way on the return at the previous time t-1, the returns are said to be autocorrelated. In…Continue
Added by Vincent Granville on July 8, 2019 at 10:25am — No Comments
Summary: The annual Burtch Works salary survey tells us a lot about which industries are using the most data scientists and the difference between higher and lower skilled data scientists. Salary increases show us whether demand is increasing, and finally we take a shot at determining which skills are most in demand.
What a difference a few years can make. We used to say that everyone loves a data scientist – and wants to be one. …Continue
Added by Vincent Granville on July 8, 2019 at 10:18am — No Comments
By Ajit Jaokar. This post is a part of my forthcoming book on Mathematical foundations of Data Science. In this post, we use the Perceptron algorithm to bridge the gap between high school maths and deep learning.
As part of my role as course director of the Artificial Intelligence: Cloud and Edge Computing at the University of Oxford, I see more students who are familiar with programming than with mathematics.
They have last learnt maths…Continue
Added by Vincent Granville on June 27, 2019 at 12:22pm — No Comments
Originally published in 2014 and viewed more than 200,000 times, this is the oldest data science cheat sheet - the mother of all the numerous cheat sheets that are so popular nowadays. I decided to update it in June 2019. While the first half, dealing with installing components on your laptop and learning UNIX, regular expressions, and file management hasn't changed much, the second half, dealing with machine learning, was rewritten entirely from scratch. It is amazing how things changed in…Continue
Added by Vincent Granville on June 6, 2019 at 8:27pm — No Comments
It will be unwise to expect you will generate lot of sales if you have significant amount of web traffic. It alone cannot be of much help in this matter. You will need to track the website metrics properly in order to take necessary measure to convert the traffic into your business prospects. You will need to analyze your website from time to time to ensure that it is not only accessible to the users but also provides all necessary guidance to show them the right way to make a…Continue
Added by Jenny Richards on June 6, 2019 at 1:30am — No Comments