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Philip Wilkinson, Ph.D.
Philip Wilkinson, Ph.D.

2.8K Followers

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Published in

Towards Data Science

·Pinned

A Complete Data Science Curriculum for Beginners

UCL Data Science Society: Introduction to Python, Data Scientists Toolkit, Data Science with Python — This year, the UCL Data Science Society aimed to create a complete Data Science curriculum with the purpose of helping other students on their Data Science journey. …

Data Science

14 min read

A Complete Data Science Curriculum for Beginners
A Complete Data Science Curriculum for Beginners
Data Science

14 min read


Published in

Towards Data Science

·Pinned

8 Data Structures every Data Scientist Should Know

From basic data structures to Abstract Data Types — As a Data Scientist, a key part of the job is to be able to understand the best way to organise and structure data so that it can be efficiently stored or accessed depending on the task. This could be for the purpose of inputting the data into a model…

Data Structures

7 min read

Eight Data Structures Every Data Scientist Should Know
Eight Data Structures Every Data Scientist Should Know
Data Structures

7 min read


Published in

Towards Data Science

·Pinned

A complete guide to git for beginners

Key commands, functionality, and usage — Git is a tool that all Data Scientists and Software Engineers should know how to use. Whether you work on a project alone or as part of a large distributed team, understanding how to effectively use Git can save you a lot of time with your projects. The benefit of…

Data Science

14 min read

A complete guide to git for beginners
A complete guide to git for beginners
Data Science

14 min read


Published in

Towards Data Science

·Pinned

An introduction to Object-Oriented Programming for Data Scientists

The basics of OOP for those who may not have come across the idea before or are wanting to know more — First of all, what is Object-Oriented Programming? This is what is known as a Programming paradigm, which essentially means that it is a specific way of doing something or structuring your code. What OOP means is that you structure your code around objects which is good for building frameworks and…

Object Oriented

6 min read

An introduction to Object-Oriented Programming for Data Scientists
An introduction to Object-Oriented Programming for Data Scientists
Object Oriented

6 min read


Published in

Towards Data Science

·Pinned

Introduction to decision tree classifiers from scikit-learn

Applying a decision tree classifier to the iris dataset — There are plenty of articles out there that explain what a decision tree is and what it does: Decision Tree Classification A Decision Tree is a simple representation for classifying examples. It is a Supervised Machine Learning where the data…medium.com The Basics: Decision Tree Classifiers An intuition for how decision trees work and are builttowardsdatascience.com

Python

10 min read

Introduction to decision tree classifiers from scikit-learn
Introduction to decision tree classifiers from scikit-learn
Python

10 min read


Published in

Python in Plain English

·Aug 17

Demystifying Context Managers in Python

A short technical guide on how and when to use them — Python has become a go-to language for developers and data scientists across the globe. Nevertheless, one of its most powerful features, context managers, often remains underutilized or misunderstood. In this short technical guide, we will dive into understanding context managers in Python, their working principles and practical applications. …

Context Managers

6 min read

Demystifying Context Managers in Python
Demystifying Context Managers in Python
Context Managers

6 min read


Published in

Towards Data Science

·Jul 18

*args, **kwargs, and Everything in Between

The fundamentals of function parameters and arguments in Python — Python has become the go-to language in Data Science for its versatility, simplicity, and powerful libraries. Functions, with their ability to encapsulate reusable code, play a key role in streamlining and enhancing the data science workflow in Python. …

Python

6 min read

*args, **kwargs, and Everything in Between
*args, **kwargs, and Everything in Between
Python

6 min read


Published in

Towards Data Science

·Jul 4

Git Tags: What Are They and How To Use Them

What are they used for, creating a local tag, how they are seen and how to delete them — In Git, a tag is a way to mark a specific point in the history of a repository. It is typically used to label important milestones or releases, such as a version, release or a major project update. They usually serve three key purposes: Release versions: Tags are commonly used…

Git

4 min read

Git Tags: What Are They and How To Use Them
Git Tags: What Are They and How To Use Them
Git

4 min read


Published in

Towards Data Science

·Mar 21

Automated Python Application Testing Using GitHub Actions

How to run automatic testing on the push command — Testing your application is a crucial step in any software development or data science workflow. Testing allows you to ensure that the code functions as expected, reduces the likelihood of bugs or errors, and increases the overall quality and reliability of the software. In some cases though testing can often…

Testing

6 min read

Automated Python Application Testing Using GitHub Actions
Automated Python Application Testing Using GitHub Actions
Testing

6 min read


Published in

dunnhumby Data Science & Engineering

·Mar 13

Deciding Where to Shop

Can Newton’s idea of gravity be used to estimate grocery store revenue? With many different brands, formats and channels to engage with, deciding where, when and how to do your grocery shop can be a complex decision. Some of us will do a regular weekly shop at a large superstore…

Data Science

10 min read

Deciding Where to Shop
Deciding Where to Shop
Data Science

10 min read

Philip Wilkinson, Ph.D.

Philip Wilkinson, Ph.D.

2.8K Followers

Data Visualisation Engineer at McLaren Racing Limited. 500,000+ views. Connect on: www.linkedin.com/in/philip-wilkinson1

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    ODSC - Open Data Science

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    Plotly

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    Attila Vágó

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    Bex T.

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    Data@Urban

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