Tarek Amr

Machine Learning Data Scientist

Tarek Amr

Hands-On Machine Learning with Scikit-Learn and Scientific Python Toolkits by Tarek Amr

Unleash Your Machine Learning Potential with my Book!

Why you need to learn machine learning from a book?

📖 Why learn machine learning from a book? Because it lays the foundation for success.

My book, "Hands-On Machine Learning with Scikit-Learn and Scientific Python Toolkits," is your practical guide to jumpstart your data science career. No need to fear complex math – I've made it accessible and engaging.

📬 Order now to supercharge your machine learning journey and unlock exciting opportunities!

Amazon GoodReads
Practical D3.js by Tarek Amr

Order my book: Practical D3

👉 This is your guide to mastering the efficient use of D3.js in professional-standard data visualization projects.

You will learn what data visualization is, how to work with it, and how to think like a D3.js expert, both practically and theoretically. You will learn how to get the data, how to clean and refine it, and how to display it in the best charts and layouts. The book is for experience Front End JavaScript Developers, as well as for Data Journalists who who have basic knowledge of HTML/CSS and some JavaScript.

📖 I co-authored this book with Rayna Stamboliyska. Order it from any of the following links

Apress Amazon
Bayesian Experimentation

Bayesian AB-Tests

🔮 Throughout the course of your career, you may need to quantify the effect of changes you make to a product or service. These change can be the introduction of a new design to a website, the creation of a new medicine, or even choosing one football player to take a penalty kick for your team over another in the World Cup final.

🎲 Traditionally, the frequentist approach prevails. However, the Bayesian approach is more intuitive and easy to explain to your stakeholders.

In this article I wrote about the Bayesian hypothesis testing approach.

Oracle Blog

URL-Based Web Page Classification using Language Models (MSc. Dissertation)

In today's world, millions of web links are shared daily through emails and social media websites. Therefore, it is crucial to have an efficient and reliable method to classify web pages based on their URLs without the necessity of visiting the actual page.

🕸 For instance, social media platforms may require a swift identification of status updates containing links to malicious websites for immediate blocking. Furthermore, classification results can be utilized in marketing research to anticipate users' preferences and interests.

🎓 Thus, the target of this research is to be able to classify web pages using their URLs only.


Quick Introduction to Reinforcement Learning

Reinforcement Learning (RL) is not as commonly used as Supervised Machine Learning. Yet, it is important to know its basics and have it as a part of your own ML toolkit

🎥 These slides have a quick introduction to RL using the Exploding Kittens Card Game.

Reinforcement Learning Slides

Behavioural Economics

After reading Richard Thaler's book, Misbehaving, I decided to summarise it. This also serves as my very quick introduction to Behavioural Economics

🎥 This slide deck have a quick introduction Behavioural Economics and its concepts

Behavioural Economics Slides

About Me

🐍 With over 10 years of experience in data science and machine learning, combined with 15 years of Python programming, I bring a strong foundation of expertise to the table.

🎓 After finishing my postgraduate degree at 🇬🇧 The University of East Anglia (UEA), I worked in a number of startups and scale-up companies in 🇪🇬 Egypt and 🇳🇱 The Netherlands.

🐾 In previous lives I used to work as an Information Security Consultant and Presales Manager. I previously volunteerd in Global Voices Online (GVO) and the Open Knowledge Foundation (OKFN). This background made me interested in the intersection between computer sciene, business strategy and writing.

🔥 In a nutshell, I am trying to challenge the old saying, "Jack of all trades, master of none".

LinkedIn Profile

Jack of all trades, Master of Machine Learning