This is not a discussion as to whether the data is flawed or not, or whether we are comparing apples to oranges or not (the way statistics are gathered in different countries). These are of course fundamental questions, but here I will only use data (provided by Google) that everyone seem to more or less agree with, and I am not questioning it…

The original version of the central limit theorem (CLT) assumes n independently and identically distributed (i.i.d.) random variables X1, ..., Xn, with finite variance. Let Sn = X…

Source: here

If you are wondering how much a data scientist earns, whether you are a hiring manager or looking for a job, there are plenty of websites…

This is part of a series featuring the following aspects of machine learning:

• Mathematics, simulations, benchmarking algorithms based on synthetic data (in short,…

In this article, I describe the various steps involved in managing a machine learning process from beginning to end. Depending on which company you work for, you may or may not be involved in all the steps. In larger companies, you typically focus on one or two specialized aspects of a project. In small companies, you may be involved in all…

As a machine learning professional, I have worked for several startups ranging from zero to 600 employees, as well as companies such as eBay, Wells Fargo, Visa and Microsoft. Here I share my experience. A brief summary can be found in my conclusions, at the bottom of this article.

It is not easy to define what a startup is. The first…

In this article, I illustrate the concept of asymmetric key with a simple example. Rather than discussing algorithms such as RSA, (still widely used, for instance to set up a secure website) I focus on a system easier to understand, based on random permutations. I discuss how to generate these random permutations and compound them, and how to…

Many of us have solid foundations in math or have an interest in learning more, and are passionate about solving difficult problems during our free time. Of course, most of us are not professional mathematicians, but we may bring some value to help solve some of the most challenging mathematical conjectures, especially the ones that can be…

This is part of a series featuring the following aspects of machine learning:

• Mathematics, simulations, benchmarking algorithms based on synthetic data (in short, experimental data science)
• Opinions, for instance about the value of a PhD in our field, or the use of some…

Orbit of the Riemann zeta function in the complex plane (see also here)

Despite my long statistical and machine learning career both in academia and in…

Source: here

Here is what I learned from practicing machine learning in business settings for over two decades, and prior to that in the academia. Back in the nineties, it was known as computational…

Source for picture: here

The first part of this list was published…

Here some off-the-beaten-path options to consider, when looking for a first job, a new job or extra income by leveraging your machine learning experience. Many were offers that came to my mailbox at some point in the last 10 years, mostly from people looking at my LinkedIn profile. Thus the importance of growing your network and visibility, write…

We describe here a methodology that applies to any statistical test, and illustrated in the context of assessing independence between successive observations in a data set. After reviewing a few standard approaches, we discuss our methodology, its benefits, and drawbacks. The data used here for illustration purposes, has known theoretical…

Source: See article #5, in section 1

Part 2 of this short series focused on fundamental techniques, see here. In this Part 3, you will find several…

There are many ways chaos is defined, each scientific field and each expert having its own definitions. We share here a few of the most common metrics used to quantify the level of chaos in univariate time series or data sets. We also introduce a new, simple definition based on metrics that are familiar to everyone. Generally speaking, chaos…

Source: here

In my previous article here, I discussed a…

Source: here

There are numerous examples in machine learning, statistics, mathematics and deep learning, requiring an algorithm to solve some complicated equations: for instance, maximum likelihood…

Source: see here

In Part 1 of this short series, I have included the most interesting articles that I wrote in the last few years. This part focuses on the business analytics / BI /…