Gabriel Berardi

Changing the Geekom A5 WiFi Card

Fri, 27 Mar 2026 00:00:00 +0000

In this blog post, I am going to explain how to change the Realtek 8852BE WiFi card that comes with the Geekom A5.

Many people (myself included) experience WiFi issues when using Linux on the Geekom A5. A lot of people report that the Realtek 8852BE WiFi card works well on Windows, but on Linux, WiFi would often suddenly disconnect and it would not be possible anymore to reconnect to the internet. Only a reboot helps in this situation.

Simple Questions, Hard Answers

Sat, 14 Sep 2024 00:00:00 +0000

When business stakeholders ask data experts seemingly simple questions, they often expect a quick and straightforward answer. On the surface, it seems like a piece of cake. But in the messy reality of data, what appears to be a simple question can quickly turn into a multi-layered onion of a problem - each layer revealing increasing complexity and ambiguity.

Example from the insurance domain:

Let’s take a practical example from the insurance industry. A sales executive asks:

Bitcoin’s Role in Achieving ESG Goals for Insurers

Sat, 21 Oct 2023 00:00:00 +0000

In recent years, in light of the growing attention given to climate change and environmental concerns, insurance companies worldwide have been increasingly focused on ESG (Environmental, Social, and Governance) objectives. Indeed, according to a survey conducted by PricewaterhouseCoopers in 2022, 85% of global insurers believe that ESG will impact all functions of their business in the years to come.

Bitcoin on the other hand, is often denounced to be “terrible for the environment” and a “contributor to climate degradation”. Media outlets oftentimes quote statistics such as:

Microinsurance – the Potential of Bitcoin and Lightning

Wed, 30 Aug 2023 00:00:00 +0000

Insurance is a market-based risk management tool that is fundamentally based on sharing and diversifying risks among a community of policyholders. It creates a safety net against unpredictable events, protecting individuals and societies from potentially hazardous financial losses. This invaluable system not only provides a sense of security to its members but also fosters innovation and exploration, encouraging humans to embrace calculated risks. Thus, insurance makes our world more resilient, fostering innovation and stability.

Is Bitcoin the Largest Insurance in the World?

Sun, 30 Jul 2023 00:00:00 +0000

In a recent article and also on a Twitter thread, American entrepreneur, investor, and influencer Anthony Pompliano has called Bitcoin ‘the largest insurance company in the world’:

His argument in the article is quite straight-forward:

Bitcoin can protect its buyers from currency debasement, sovereign default or undisciplined monetary and fiscal policy. In order to receive this risk protection, someone has to pay the current Bitcoin price, which could be considered a one-time insurance premium. The earlier they buy this insurance, the cheaper it is.
Instead of relying on an insurance company to honor their policy during a crisis, Bitcoin offers a digitized solution that doesn’t require you to file a claim, eliminating the need for trust.
Pompliano even goes further in his article. According to him, Bitcoin offers insurance for previously uninsurable risks, like high inflation or government seizure of assets.
In summary, Bitcoin as a $500+ billion insurance product could be considered the largest insurance in the world.

Bitcoin as an insurance? Even the largest insurance in the world? It is an intriguing thought, which many in the Bitcoin community seem to share. Let’s take a closer look at this.

Bitcoin and Insurance – Why Is No One Talking About This?!

Wed, 14 Jun 2023 00:00:00 +0000

The first Bitcoin was mined in 2009 – only 14 years ago. In these 14 years, Bitcoin has developed from a curious experiment ran by a small group of cypherpunks into a global phenomenon. Its journey from obscurity to mainstream recognition has been nothing short of remarkable, as has been reflected not only by its price, but by the growing computing power securing this global network. Bitcoin is on its way to disrupt traditional financial systems, challenging the centralized control of money and empowering individuals with financial sovereignty.

Data Leakage in Machine Learning

Tue, 01 Dec 2020 00:00:00 +0000

Recently, I read a thread on Twitter about several Machine Learning papers that contained severe cases of data leakage. The authors of the papers seemed unaware of this phenomenon and therefore trained models that performed exceptionally well. Unfortunately, this was mainly due to data leakage.

Not many beginners are aware of this problem and in my opinion, not many courses emphasize this issue early enough. Therefore, I would like to tell you all the things you need to know about data leakage and some ways to prevent it in this post.

Detect Forged Banknotes with a Logistic Regression

Tue, 01 Sep 2020 00:00:00 +0000

Counterfeit money is a real problem both for individuals and for businesses. Counterfeiters constantly find new ways and techniques to produce fake banknotes, that are essentially indistinguishable from real money. At least for the human eye!

Identifying forged banknotes is a typical example of a binary classification task in Machine Learning. If we have enough data of both real and forged banknotes, we can use this data to train a model that can classify new banknotes as either real or fake.

Linear and Logistic Regression

Wed, 01 Jul 2020 00:00:00 +0000

Linear and Logistic regression are among the most elementary algorithms for supervised learning. Supervised Learning describes the situation where we deal with labelled data, which means that we have labelled inputs and a target variable.

Despite the fact that both have the word “regression” in their name, only one of them is typically being used for solving regression problems!

Let’s see how they work!

Linear Regression

Linear regression is possibly the easiest, most intuitive way of making a quantitative prediction. The relationship between an independent and a dependent variable is assumed to be linear, meaning that the dependent variable can be predicted using a linear function of the independent variable. For example:

How to Create a Racing Bar Chart with Python

Fri, 01 May 2020 00:00:00 +0000

After reading this article from Pratap Vardhan with great interest, I wanted to build my own version of a Bar Chart Race that is smoother and a bit more beautiful. The biggest improvement is the interpolation (or augmentation) of the available data points in order to make the animation smoother.

Here is the Bar Chart Race we are going to build in this article:

For the purpose of this demonstration, we are going to use a GDP per capita forecast dataset provided by the OECD. You can find the original dataset here.

k-Nearest Neighbors

Fri, 01 May 2020 00:00:00 +0000

k-Nearest Neighbors, or k-NN as I am going to call it from now on, is one of the easiest algorithms to solve classification tasks. It can be used for regression problems as well, but I am going to focus on the more common use case of classification in this post.

In a nutshell, k-NN will assign a new data point to the class that the majority of its k neighbours in the training set belong to. Let’s use another coffee-related example to see how that works.

Simple Facial Recognition with OpenCV

Fri, 01 May 2020 00:00:00 +0000

Have you ever seen some cool applications of computer vision tools, like this the one below?

Perhaps your phone’s camera can autofocus on faces, or maybe you have uploaded a photo on a social media platform and it automatically recognized the person on the image?

These are facial recognition applications and they all rely on Machine Learning. In this post, we are going to use a very easy package called OpenCV to build our own facial recognition program!

Where to eat in Munich?

Fri, 01 May 2020 00:00:00 +0000

I recently moved to a new city - Munich! I live in a very calm area, but soon realized that the neighbourhood is not really the best when it comes to eating outside. So, I decided to try to analyse review data from the web to find out which area is most compelling for me and other foodies. I scraped online reviews, cleaned the data and then visualized it on a map, showing the average rating of restaurants in different areas in Munich.

Scrape a Book Shop with BeautifulSoup

Sun, 01 Mar 2020 00:00:00 +0000

Web Scraping is the automated process of extracting data from websites. This is commonly done by retrieving the HTML code of a website through a request and then extracting the information hidden in the HTML code programmatically. This is especially convenient when there is no API available to you!

There has been a lot of discussion going on about the legality and ethics of Web Scraping, which I do not want to get into in this article. You can check out this Wikipedia article and this blog post, if you want to know more about that.

k-Means Clustering

Wed, 01 Jan 2020 00:00:00 +0000

The k-means algorithm is used to divide unlabeled data into categories or classes, in order to draw useful conclusions from the resulting clusters.

Let’s take a look at an imaginary dataset of n = 18 observations of different coffee brands. Note that we would never actually use the k-means algorithm on such a small data set.

We plot the price of the coffee vs. the rating obtained by customers:

About Me

Mon, 01 Jan 0001 00:00:00 +0000

I am originally born and raised in Switzerland 🇨🇭 but life has brought me to Germany 🇩🇪 where I am living and working in the beautiful City of Munich. For the past 8 years, I have been working in different roles in Insurance - from core insurance functions in sales, to business intelligence and data analytics.

After completing my Bachelor degree in Insurance and Finance, I had developped a strong interest in all things data and tech. I had already taught myself how to code with Python, but I definitely wanted to learn more about data analytics, which is why I decided to pursue a Masters degree in Data Analytics from the University of Glasgow.

Imprint/Impressum

Mon, 01 Jan 0001 00:00:00 +0000

Responsible for content according to § 5 TMG (Telemediengesetz):

Gabriel Berardi, Balanstr. 92, Munich

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Editorial Responsibility:

Gabriel Berardi, Balanstr. 92, Munich

Disclaimer:

This newsletter and website are intended for informational purposes only and do not constitute legal, financial, or insurance advice.

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Ressources

Mon, 01 Jan 0001 00:00:00 +0000

📝 Articles

Sometimes I like to write stuff, such as:

aticles on Data Topics
articles on Technology
articles on Bitcoin

🔓 Recommended FOSS

I am a huge fan and supporter of FOSS (Free and Open Source Software). Having a global communtiy of highly talented people working together to develop great software tools is simply a wonderful idea.

Here’s a list of open source software projects that I have used in the past or that I am still using and supporting: