By Rebecca Vickery Originally published on EDF’s Energywise Blog Each year EDF runs a two-year data and technology scheme where graduates undertake work placements and tailored training to develop a range of skills from the fields of software engineering, data engineering and data science. …

5 resources for learning the skill that no one will teach you — There are tons of training materials, courses and articles available about how to become a Data Scientist. Once you start working in the field the transition to a Senior Data Scientist should naturally occur as you gain more experience and skills. For many Data Scientists the natural next step after…

A quick reference guide to 5 common algorithms — The “no free lunch” theorem for machine learning states that there is no single machine learning algorithm that can solve all types of machine learning problems. Machine learning tasks can vary widely and the choice of algorithm will depend on things such as the size, dimensionality and sparsity of the…

What are the strategies? How and when should you use them? — The goal of a machine learning model is to learn general patterns from specific examples. In real life all data contains a degree of random variation and noise. …

Quickly analyse and summarise your data with these Python tools — Data profiling is one of the first steps in any data science project. It is a form of exploratory data analysis which seeks to analyse, describe and summarise a dataset to gain an understanding of both its quality and fundamental characteristics. The data profiling task is used to inform further…

Understand how and when to apply common preprocessing techniques — Machine learning algorithms learn patterns that exist in a set of features and use these patterns to predict a given target variable for new unknown data. The resulting trained model is essentially a mathematical function that successfully maps the values of X (the features) to the unknown value of y…

Get started with machine learning using Snowpark Python — If you are working as a Data Scientist in a business setting you will extract much of your data for machine learning from a data warehouse or data lake. …

Get started with your machine learning journey for free — There are many ways to get started with studying machine learning. I have previously written a lot about how to design your own curriculum and roadmap as an alternative to taking courses. This approach allows you to pick and choose free, or low-cost, resources from across the internet that suit…

How to install, set up, and use Poetry to manage your data science projects — Reproducibility is an important aspect of data science. When we talk about reproducibility in data science we refer to the ability to independently recreate the results of a project either by yourself at a later point in time or by a colleague. Having processes that ensure reproducibility builds trust in…