The Hark Blog

Timeseries Stationarity

Timeseries Stationarity

This blog post discusses the importance of stationarity in timeseries data when performing analysis or generating forecasts. Non-stationary data can pose challenges for accurate forecasting, but transformations such as differencing, Box-Cox, and Yeo-Johnson can help make data stationary. These techniques can help with effective planning and implementation of energy management policies.

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Timeseries Stationarity

Timeseries Stationarity

This blog post discusses the importance of stationarity in timeseries data when performing analysis or generating forecasts. Non-stationary data can pose challenges for accurate forecasting, but transformations such as differencing, Box-Cox, and Yeo-Johnson can help make data stationary. These techniques can help with effective planning and implementation of energy management policies.

Read More
Hexadecimal Blog Post Featured Image (1)

What The Hex: Demystifying Hex Codes

Whether you’re a former Myspace tinkerer or a seasoned web developer who deals daily with colour on the web, you’ve probably come across hex codes before, but how much do you know about this strange-looking combination of numbers and letters? If the answer is not very much, check this out.

data science image

Understanding the Bias Variance Trade-Off

The bias-variance trade-off is a fundamental concept in machine learning and statistics that refers to the trade-off between a model’s ability to fit the training data well (low bias) and its ability to generalise to unseen data (low variance).

iot project planning

Why do IoT projects fail and what can be done to ensure success?

The internet of things (IoT) is best known for unlocking new business opportunities by transforming the way people and machines work. In today’s world, data is the key to a business’s success; IoT deployments can provide critical data to any device such as a phone, tablet or computer within seconds to help businesses improve performance.

Hark at EMEX 2022

Energy Management Lessons we learnt at EMEX 2022

Last week, we took a trip to the London ExCel Centre for EMEX, the net zero and energy management expo. The event this year stood out in a way that previous years couldn’t have; the pressure of the energy crisis added a resounding feeling to the event which spurred some important conversations. I wanted to write something to reflect on some of the excellent questions, demos and chats that took place on the Hark wind turbine stand (as seen in the video below).

Splitting data

Splitting data into ‘train’, ‘validation’ and ‘test’ sets

When developing and deploying machine learning models, it’s important that we split the dataset into ‘train’, ‘validation’, and ‘test’ datasets. This protects against an overfitted model, and helps ensure results are generalised. In this blog post we will look in to how to split the data, and why.

project management

8 Project management methodologies for delivering IoT deployments

Internet Of Things (IoT), is no longer a tech buzzword but an advanced everyday reality describing a multitude of technologies that connect assets and objects to the internet. Before you start deploying IoT solutions or deployments, it’s vital to understand what project management methodology to use, as all IoT projects are different and will require slightly different approaches.

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