# Articles
This section shows the article I wrote for different online websites.

***

## Achievements
Before presenting my articles, I'd like my achievements talk for me. I believe this is a good way for you to understand the quality of my work and the results we can get together:
- **Selected by NVIDIA**: Given my expertise and the articles I created in the field of Articifial Intelligence, I've been selected by NVIDIA for a pre-briefing where they presented the Polars GPU engine in preview:
    ```{figure} images/articles/nvidia.png
    :alt: Email from NVIDIA to Federico Trotta for invitation.
    :align: center

    *The invitation to the pre-briefing*
    ```

    And here's the article I wrote for them: [Accelerating Polars with RAPIDS cuDF](https://dev.to/federicotrotta/accelerating-polars-with-rapids-cudf-3833)

- **Spotted by DZONE**: One of my articles on Data Engineering has been featured on the DZone main page on the 14th of June 2024 as a spotlighted article (see it [here](#my-articles-for-dzone))

- **Recognized as one of the most read TDS's contributors**: I was recognized as one of the most read authors by Towards Data Science:
    ```{figure} images/articles/tds.png
    :alt: Email from Towadards Data Science to Federico Trotta for recognition.
    :align: center

    *The email from Towards Data Science to Federico Trotta for recognition.*
    ```

- **Owner of the documentation chapter for the "The open source book"**: I've been the owner of the chapter abot the documentation for the book "The open source book" ("Il libro open source" in Italian) which is an [italian manual for developers](https://github.com/Il-Libro-Open-Source).

***

## My articles for Towards Data Science
With tens of published articles, I started my Technical Writing career by collaborating with the established publication [Towards Data Science](https://towardsdatascience.com/).

I have published articles about Python programming, statistical concepts for Data Scientists, and Machine Learning.

Here's the list of my best articles:

### Tutorials
- [How to Convert a CSV file into an XLSX one with Python and Pandas](https://towardsdatascience.com/how-to-convert-a-csv-file-into-an-xlsx-one-with-python-and-pandas-27aabc279d69?source=your_stories_page-------------------------------------)
- [How To Deal With Missing Values in Data Science](https://towardsdatascience.com/how-to-deal-with-missing-values-in-data-science-9e5a56fbe928?source=your_stories_page-------------------------------------)
- [How to Perform Feature Selection in a Data Science Project](https://towardsdatascience.com/how-to-perform-feature-selection-in-a-data-science-project-591ba96f86eb)
- [How To Detect Outliers in a Data Science Project](https://towardsdatascience.com/how-to-detect-outliers-in-a-data-science-project-17f39653fb17?source=your_stories_page-------------------------------------)
- [How to Effectively Start Coding in the Era of ChatGPT](https://medium.com/towards-data-science/how-to-effectively-start-coding-in-the-era-of-chatgpt-cfc5151e1c42)
- [How To Solve Python Dependency Issues With Anaconda On Windows](https://medium.com/towards-data-science/how-to-solve-python-dependency-issues-with-anaconda-on-windows-d5033c9d2f9a)


### General programming
- [Loops and statements in Python: A deep understanding (with examples)](https://towardsdatascience.com/loops-and-statements-in-python-a-deep-understanding-with-examples-2099fc6e37d7?source=your_stories_page-------------------------------------)
- [Python Loops: A Complete Guide On How To Iterate in Python](https://towardsdatascience.com/python-loops-a-complete-guide-on-how-to-iterate-in-python-b29e0d12211d)
- [Python Classes Made Easy: The Definitive Guide to Object-Oriented Programming](https://towardsdatascience.com/python-classes-made-easy-the-definitive-guide-to-object-oriented-programming-881ed609fb6)
- [Mastering Modular Programming: How to Take Your Python Skills to the Next Level](https://towardsdatascience.com/mastering-modular-programming-how-to-take-your-python-skills-to-the-next-level-ba14339e8429)
- [Python Lists: The Definitive Guide for Working With Ordered Collections of Data](https://towardsdatascience.com/python-lists-the-definitive-guide-for-working-with-ordered-collections-of-data-53b06a194826)
- [Leveraging the Power of “5S” for Clean and Reusable Code](https://towardsdatascience.com/leveraging-the-power-of-5s-for-clean-and-reusable-code-44e1dc466af2)


### Data science
- [What is the Difference between a Barplot and a Histogram?](https://towardsdatascience.com/what-is-the-difference-between-a-barplot-and-a-histogram-e62d0e532e7d)
- [Two Methods for Performing Graphical Residuals Analysis](https://towardsdatascience.com/two-methods-for-performing-graphical-residuals-analysis-6899fd4c78e5)
- [The Difference Between Correlation and Regression](https://towardsdatascience.com/the-difference-between-correlation-and-regression-134a5b367f7c?source=your_stories_page-------------------------------------)
- [Understanding l1 and l2 Regularization](https://towardsdatascience.com/understanding-l1-and-l2-regularization-93918a5ac8d0?source=your_stories_page-------------------------------------)
- [What is a Trained Model?](https://towardsdatascience.com/what-is-a-trained-model-5c872cfa8448?source=your_stories_page-------------------------------------)
- [5 Python Libraries to Learn to Start Your Data Science Career](https://towardsdatascience.com/5-python-libraries-to-learn-to-start-your-data-science-career-2cd24a223431)
- [Mastering the Art of Regression Analysis: 5 Key Metrics Every Data Scientist Should Know](https://towardsdatascience.com/mastering-the-art-of-regression-analysis-5-key-metrics-every-data-scientist-should-know-1e2a8a2936f5)
- [Make Your Tabular Data Stand Out via CLI With These Tips and Tricks](https://towardsdatascience.com/make-your-tabular-data-stand-out-via-cli-with-these-tips-and-tricks-a21f276b7ba9)
- [Please: No More Flipping Coins in Data Science](https://towardsdatascience.com/please-no-more-flipping-coins-in-data-science-f21e893d4fbd)
- [Mastering Linear Regression: The Definitive Guide For Aspiring Data Scientists](https://medium.com/towards-data-science/mastering-linear-regression-the-definitive-guide-for-aspiring-data-scientists-7abd37fcb9ed)
- [The Myth Of p-values: Why They’re Not the Holy Grail in Data Science](https://towardsdatascience.com/the-myth-of-p-values-why-theyre-not-the-holy-grail-in-data-science-a6636e27e489)
- [Classification Metrics: The Complete Guide For Aspiring Data Scientists](https://medium.com/towards-data-science/classification-metrics-the-complete-guide-for-aspiring-data-scientists-9f02eab796ae)
- [Unleashing the Power of Prompt Engineering for Data Scientists](https://medium.com/towards-data-science/unleashing-the-power-of-prompt-engineering-for-data-scientists-16b6d1f2bf85)
- [The Data Scientist’s Toolbox: Leveraging scikit-learn’s Top Features for Success](https://towardsdatascience.com/the-data-scientists-toolbox-leveraging-scikit-learn-s-top-features-for-success-d69a899267c5)
- [A Gentle Introduction To Generative AI For Beginners](https://medium.com/towards-data-science/a-gentle-introduction-to-generative-ai-for-beginners-8c8752085900)
- [Use Pandas Data Frames More Effectively with the Top 7 Column Operations](https://towardsdatascience.com/dominate-pandas-data-frames-with-the-top-7-column-operations-2a11521e9e2d)
- [Beyond Numpy and Pandas: Unlocking the Potential of Lesser-Known Python Libraries](https://towardsdatascience.com/beyond-numpy-and-pandas-unlocking-the-potential-of-lesser-known-python-libraries-86d2bdc4d230)
- [Building Interactive Data Visualizations in Python: An Introduction to Plotly](https://towardsdatascience.com/building-interactive-data-visualizations-in-python-an-introduction-to-plotly-3ffdd920fc63)

***

## My articles for Bright Data
[Bright Data](https://brightdata.com/) is a leading company in the field of web scraping. 

Read my articles:
- [How to Bypass CAPTCHAs With Puppeteer](https://brightdata.com/blog/web-data/bypass-captchas-with-puppeteer)
- [Web Scraping With Jupyter Notebooks](https://brightdata.com/blog/web-data/web-scraping-with-jupyter-notebooks)
- [Web Scraping With Selenium Wire in Python](https://brightdata.com/blog/web-data/web-scraping-with-selenium-wire)
- [Scrapy vs. Requests: Which One Is Better For Web Scraping?](https://brightdata.com/blog/web-data/scrapy-vs-requests)
- [Scrapy vs Pyspider: Which One Is Better for Web Scraping?](https://brightdata.com/blog/web-data/scrapy-vs-pyspider)
- [How to Rotate Proxies in Python](https://brightdata.com/blog/proxy-101/rotate-proxies-in-python)
- [A Guide to Data Analysis With Python in 2025](https://brightdata.com/blog/web-data/analysis-with-python)
- [Web Scraping With Parsel in Python: 2025 Guide](https://brightdata.com/blog/web-data/web-scraping-with-parasel)
- [Web Scraping With Scrapy Splash: Step-By-Step Guide](https://brightdata.com/blog/web-data/web-scraping-with-scrapy-splash)
- [How to Use Web Scraping for Machine Learning](https://brightdata.com/blog/web-data/web-scraping-for-machine-learning)
- [The 5 Best CAPTCHA Proxies of 2025](https://brightdata.com/blog/proxy-101/best-captcha-proxies)
- [What Is Supervised Fine-Tuning in LLMs?](https://brightdata.com/blog/ai/supervised-fine-tuning)
- [What Is Zero-Shot Classification?](https://brightdata.com/blog/ai/zero-shot-classification)
- [Web Scraping With Botright: 2025 Guide](https://brightdata.com/blog/web-data/web-scraping-with-botright)
- [What Is MoE? A Deep Dive Into a Popular AI Architecture](https://brightdata.com/blog/ai/mixture-of-experts)
- [Fine-Tuning Llama 4 with Fresh Web Data for Better Results](https://brightdata.com/blog/ai/fine-tuning-llama-4-with-web-data)
- [AI-Powered Web Scraping in Dify via a No-Code Workflow](https://brightdata.com/blog/ai/web-scraping-with-dify)
- [Using Dify and Bright Data for Web Search](https://brightdata.com/blog/ai/dify-serp-scraping)
- [How To Fine-Tune GPT-4o With a Web Scraper API Using n8n](https://brightdata.com/blog/ai/fine-tune-gpt-4o-using-n8n)
- [Top 10 MCP Servers to Improve Your AI Workflows](https://brightdata.com/blog/ai/best-mcp-servers)
- [Best Web Scraping Methods for JavaScript-Heavy Sites](https://brightdata.com/blog/web-data/scraping-js-heavy-websites)

***

## My articles for The Web Scraping Club
[The Web Scraping Club](https://substack.thewebscraping.club/) is a weekly Substack about web scraping, with news, examples, tutorials and code from [Pierluigi Vinciguerra](https://www.linkedin.com/in/pierluigivinciguerra/).

Read my articles:
- [Optimizing Python Scripts for High-Traffic Websites](https://substack.thewebscraping.club/p/scraping-high-frequency-python)
- [The Framework That Won't Quit: Scrapy's Continued Relevance in Data Extraction](https://substack.thewebscraping.club/p/scrapy-ten-years-of-scraping-framework)
- [Comparing Residential And Mobile Proxies for Anti-Bot Evasion](https://substack.thewebscraping.club/p/differences-residential-mobile-proxies)
- [Machine learning models for detecting bot detection triggers](https://substack.thewebscraping.club/p/machine-learning-for-detecting-bots)
- [Predictive Analytics Using Scraped Data](https://thewebscrapingclub.substack.com/p/predictive-analytics-web-scraped-data)

***

## My articles for FloppyData
[FloppyData](https://floppydata.com/) is a proxy provider.

Read my articles:
- [Types of Proxies: Which One Is Best?](https://floppydata.com/blog/types-of-proxies-which-one-is-best/)
- [What Are Mobile Proxies? How Do They Work & How to Use Them?](https://floppydata.com/blog/what-are-mobile-proxies-how-do-they-work-how-to-use-them/)
- [Setting Up FloppyData Proxy With Selenium in Python](https://floppydata.com/blog/setting-up-floppydata-proxy-with-selenium-in-python/)

***

## My articles for n8n
[N8n](https://n8n.io/) is a low-code automation tool that helps developers save time by creating stunning automations.

Read my articles:
- [How to make a Slack bot: Python vs. n8n Guide](https://blog.n8n.io/how-to-make-slack-bot/) 
- [12 workflow automation tools to automate your workflows](https://blog.n8n.io/workflow-automation-tools/)
- [Getting started with CRM automation: Essential guide & templates included](https://blog.n8n.io/how-to-get-started-with-crm-automation-and-no-code-workflow-ideas/)
- [Top 7 Embedded iPaaS Solutions: Choosing the Right Fit for Your Organization](https://blog.n8n.io/embedded-ipaas/)
- [Top 8 open-source Zapier alternatives for workflow automation](https://blog.n8n.io/open-source-zapier/)
- [The 20 best LLMs for coding (+ free workflow templates)](https://blog.n8n.io/best-llm-for-coding/)
- [15 Practical AI Agent Examples to Scale Your Business in 2025](https://blog.n8n.io/ai-agents-examples/)

:::{important}
“The 20 best LLMs for coding (+ free workflow templates) has ranked in the first page in Google.
:::

```{figure} images/articles/best_llms_for_coding.png
:alt: "The 20 best LLMs for coding (+ free workflow templates)" by Federico Trotta .
:align: center

*"The 20 best LLMs for coding (+ free workflow templates)" in Google's first page*
```

***


## My articles for Codemotion
[Codemotion](https://www.codemotion.com/) is an Italian firm that helps developers grow.

I wrote the following articles for the English magazine:

- [Unsupervised Learning in Python: A Gentle Introduction to Clustering Techniques for Discovering Patterns](https://www.codemotion.com/magazine/ai-ml/machine-learning/clustering-python-patterns/)
- [Data Analysis Made Easy: Mastering Pandas for Insightful Results](https://www.codemotion.com/magazine/data-science/data-analysis-made-easy-mastering-pandas-for-insightful-results/)
- [Python and Databricks: A Dynamic Duo for Data Dominance](https://www.codemotion.com/magazine/data-science/python-and-databricks-a-dynamic-duo-for-data-dominance/)
- [Python: The Versatile Programming Language That Captivates Everyone](https://www.codemotion.com/magazine/languages/python/)

And the following articles for the Italian magazine:
- [Creative Coding: Come Creare Opere d’Arte Programmando](https://www.codemotion.com/magazine/it/backend-it/creative-coding-come-creare-splendide-opere-darte-programmando/)
- [La gestione degli errori resa semplice: una introduzione in Python](https://www.codemotion.com/magazine/it/backend-it/gestione-errori-python/)
- [Apprendimento Non Supervisionato in Python: Una Introduzione alle Tecniche di Clustering per Scoprire i Pattern](https://www.codemotion.com/magazine/it/linguaggi-programmazione/introduzione-alle-tecniche-di-clustering/)
- [Python e DataBricks: la giusta accoppiata per dominare i dati](https://www.codemotion.com/magazine/it/data-science-it/python-e-databricks-la-giusta-accoppiata-per-dominare-i-dati/)
- [L’analisi dei dati resa semplice: padroneggia Pandas per ottenere risultati dai tuoi dati](https://www.codemotion.com/magazine/it/data-science-it/analisi-dei-dati-pandas/)
- [Come programmare con Python: Il linguaggio versatile che conquista tutti](https://www.codemotion.com/magazine/it/linguaggi-programmazione/programmare-con-python/)

### Codemotion for Istituto Poligrafico Zecca dello Stato e Politecnico di Bari
I contributed to writing an article on a study made by Istituto Poligrafico Zecca dello Stato and Politecnico di Bari about the creation of a knowledge graph of the whole Italian regulatory database:
-  [Come Realizzare un Knowledge Graph dell’intera Banca Dati Normativa Italiana](https://www.codemotion.com/magazine/it/data-science-it/knowledge-graph-dellintera-banca-dati-normativa-italiana/)

***

## My articles for Semaphore CI
[Semaphore](https://semaphoreci.com/) helps technology companies achieve better results.

Read my articles:
- [How to Handle Imbalanced Data for Machine Learning in Python](https://semaphoreci.com/blog/imbalanced-data-machine-learning-python)
- [Flaky Tests in Machine Learning: Challenges and Countermeasures](https://semaphoreci.com/blog/flaky-tests-machine-learning)
- [Unlocking Efficiency: 3 AI Tools for Automatic Software Documentation](https://semaphoreci.com/blog/ai-tools-software-documentation)
- [Keeping Self-Hosted LLM Costs Down: Best Practices and Tips](https://semaphoreci.com/blog/llm-cost)
- [Unit Testing vs. Integration Testing: Test Automation Basics](https://semaphoreci.com/blog/unit-testing-vs-integration-testing)
- [The Best AI Coding Assistants For 2025](https://semaphore.io/blog/ai-coding-assistants)
- [How to Use AI to Reduce Technical Debt](https://semaphore.io/blog/ai-technical-debt)

***

## My articles for Stack Abuse
[Stack Abuse](https://stackabuse.com/) is a firm that helps developers through programming tutorials and courses.

Read my articles:
- [Python Dictionary Comprehension: A Fast and Flexible Way to Build Dictionaries](https://stackabuse.com/python-dictionary-comprehension-a-fast-and-flexible-way-to-build-dictionaries/)
- [The Power of Indexing: Boosting Data Wrangling Efficiency with Pandas](https://stackabuse.com/the-power-of-indexing-boosting-data-wrangling-efficiency-with-pandas/)
- [Data Integrity: How OrderedDict Preserves Key Order in Python](https://stackabuse.com/data-integrity-how-ordereddict-preserves-key-order-in-python/)
- [Finding Numbers in Various Data Types in Python](https://stackabuse.com/finding-numbers-in-various-data-types-in-python/)

***

## My articles for Bacalhau
[Bacalhau](https://www.bacalhau.org/) is a platform for fast, cost efficient, and secure computation that enables users to run compute jobs where the data is generated and stored.

Read my articles:
- [Bacalhau v1.7.0 - Day 2: Scaling Your Compute Jobs with Bacalhau Partitioned Jobs](https://blog.bacalhau.org/p/bacalhau-v170-day-2-scaling-your)
- [Bacalhau v1.7.0 - Day 4: Using AWS S3 Partitioning With Bacalhau](https://blog.bacalhau.org/p/bacalhau-v170-day-4-using-aws-s3)
- Kubernetes vs Nomad vs Bacalhau: Which Orchestrator is Right for Your Data?:
    - [Website version](https://www.expanso.io/kubernetes-vs-nomad-vs-bacalhau)
    - [Newsletter version](https://blog.bacalhau.org/p/k8s-vs-nomad-vs-bacalhau-choosing)
- [Your Fast Track to Bacalhau: Local Development via Docker-in-Docker](https://blog.bacalhau.org/p/your-fast-track-to-bacalhau-local)
- [Why 80% of Your Data Should Never Hit the Cloud](https://www.expanso.io/why-80-of-your-data-should-never-hit-the-cloud)
- [Why Cloud-Centric Architectures Are Breaking Under Data Scale](https://blog.bacalhau.org/p/why-cloud-centric-architectures-are)

***

## My articles for Kestra
[Kestra](https://kestra.io) is an orchestration tool that simplifies business-critical workflows.

Read my articles:
- [How Orchestration Can Optimize Your Engineering Processes](https://kestra.io/blogs/2024-09-18-what-is-an-orchestrator)
- [Kestra vs. Popular CI/CD Tools: When to Choose an Orchestration Solution](https://kestra.io/blogs/2024-10-17-cd-cd-kestra-comparison)

***

## My articles for AppSignal
[AppSignal](https://blog.appsignal.com/) has recently opened its doors to Python articles. 

Read my articles:
- [Ways to Optimize Your Code in Python](https://blog.appsignal.com/2025/05/28/ways-to-optimize-your-code-in-python.html)
- [How to use Lambda Functions in Python](https://blog.appsignal.com/2024/10/16/how-to-use-lambda-functions-in-python.html)
- [How to use Regular Expressions in Python](https://blog.appsignal.com/2025/01/15/how-to-use-regular-expressions-in-python.html)

:::{important}
"“How to use Regular Expressions in Python” has been also featured and mentioned by [pip trends](https://www.linkedin.com/feed/update/activity:7295125939963736064/?trk=viral_mention) on LinkedIn.
:::

```{figure} images/articles/pip_trends_regular_expressions.png
:alt: "How to use Regular Expressions in Python" by Federico Trotta mentioned by pip trends.
:align: center

*"How to use Regular Expressions in Python" mentioned by pip trends*
```
- [An Introduction to Flask-SQLAlchemy in Python](https://blog.appsignal.com/2025/02/26/an-introduction-to-flask-sqlalchemy-in-python.html)
- [An Introduction to Testing in Python Flask](https://blog.appsignal.com/2025/04/02/an-introduction-to-testing-in-python-flask.html)

:::{important}
"“An Introduction to Testing in Python Flask” has been also featured and mentioned by [pip trends](https://www.linkedin.com/posts/pip-trends_an-introduction-to-testing-in-python-flask-activity-7321374906854645760-DNuc?utm_source=share&utm_medium=member_desktop&rcm=ACoAACkQex8BI3RNrqnOe_3FQSORgphWYeoO-R4) on LinkedIn.
:::

```{figure} images/articles/pip_trends_testing.png
:alt: "An Introduction to Testing in Python Flask" by Federico Trotta mentioned by pip trends.
:align: center

*"An Introduction to Testing in Python Flask" mentioned by pip trends*
```
- [Using JWTs in Python Flask REST Framework](https://blog.appsignal.com/2025/04/30/using-jwts-in-python-flask-rest-framework.html)
- [Flask or Django: Which One Best Fits Your Python Project?](https://blog.appsignal.com/2025/06/25/flask-or-django-which-best-fits-your-python-project.html)
- [How to Use MongoDB in Python Flask](https://blog.appsignal.com/2025/07/02/how-to-use-mongodb-in-python-flask.html)

***

## My articles for DZone
I had the privilege to co-author the following articles with [Karin Wolok](https://www.projectelevate.io/):
- [An Introduction to Stream Processing](https://dzone.com/articles/an-introduction-to-stream-processing)
- [Choosing The Right Stream Processing System: A Comprehensive Guide](https://dzone.com/articles/choosing-the-right-stream-processing-system)
- [Exploring The Dynamics of Streaming Databases](https://dzone.com/articles/exploring-the-dynamics-of-streaming-databases)

:::{important}
"Exploring The Dynamics of Streaming Databases" has been featured as DZONE's top article in the daily digest newsletter.
:::

:::{important}
"Exploring The Dynamics of Streaming Databases" has been also featured on the DZone main page on the 14th of June 2024 as a spotlighted article.
:::

```{figure} images/articles/DZone_spotlight.png
:alt: "Exploring The Dynamics of Streaming Databases" by Federico Trotta on DZone's main page.
:align: center

*"Exploring The Dynamics of Streaming Databases" on DZone's main page*
```

***

## My articles for Dev.to
[Dev.to](https://dev.to/federicotrotta) is "A constructive and inclusive social network for software developers".

Read my articles:
- [Serverless Cost Optimization Three Key Strategies](https://dev.to/federicotrotta/serverless-cost-optimization-three-key-strategies-442f)
- [Pandas reset_index(): How To Reset Indexes in Pandas](https://dev.to/federicotrotta/pandas-resetindex-how-to-reset-indexes-in-pandas-475b)
- [How To Easily Remove a Password From a PDF file](https://dev.to/federicotrotta/how-to-easily-remove-a-password-from-a-pdf-file-158b)
- [How To Create a Repository in GitHub](https://dev.to/federicotrotta/how-to-create-a-repository-in-github-kd6)
- [How to calculate RGB values in Python](https://dev.to/federicotrotta/how-to-calculate-rgb-values-in-python-3ph5)
- [How to Use Proxies in Python](https://dev.to/federicotrotta/how-to-use-a-proxy-in-python-1278)

***

## My article for Butler Scientifics
Here's my contribution to [Butler Scientifics](https://www.butlerscientifics.com/), a Spanish firm developing AutoDiscovery, a software that automates the discovery phase when analyzing data:
- [Unlock the Power of Automation: Why Automating Data Exploration is Essential for Your Efficiency](https://www.butlerscientifics.com/single-post/unlock-the-power-of-automation-why-automating-data-exploration-is-essential-for-your-efficiency)

***

## My articles for Planeta ChatBot
[Planeta ChatBot](https://planetachatbot.com/) translated into Spanish and published on their website some of the articles I wrote for Towards Data Science.

Read them [here](https://planetachatbot.com/author/federico-trotta/).

***

## My article for business.com
I'had the privilege to help business.com refactor an article about web scraping with Powershell by provide insights on my experience. Read it here:
- [How to Create a Web Scraping Tool in PowerShell](https://www.business.com/articles/create-web-scraping-tool-in-powershell/)

***

## Repurposed articles from KdNuggets
[KDnuggets](https://www.kdnuggets.com/) repurposed some of the articles I wrote for Towards Data Science: read them [here](https://www.kdnuggets.com/author/federico-trotta).

I've also been featured [here](https://www.kdnuggets.com/2023/n31.html) and mentioned [there](https://www.kdnuggets.com/2023/n21.html).