How not to fail at machine learning before you even begin

Mar 12, 2021 | Nyheter

Artificial intelligence is transforming the world and creating enormous value for those that use it well. It’s exciting. But for most people AI is a bit mysterious, and they don’t know what it looks like in practice or how to start using it themselves. Data, expertise and enthusiasm are crucial for the success of a machine learning project, but without proper scoping and planning you will fail before you even begin.


How to scope and plan machine learning projects

Are you itching to bring AI into your own domain but don’t know where to start? Or have you already started on a machine learning project but feel lost and overwhelmed?

One of the most important tasks we do as machine learning consultants is to help our customers scope and plan their machine learning projects.

Many of our customers, even if they’ve already collected the data they need, don’t know where to start. And even the most experienced data scientist can spend months lost down rabbit holes or perfecting a model that solves the wrong problem.

This is why scoping and planning is so important. Being clear on your goal and how you will reach it right from the outset is crucial to the success of your project.

Do you know the most common pitfalls?

For every success story in machine learning there are tens of projects that fizzle out, largely because they were not well-planned. Without proper planning, you could waste valuable time, resources and money. Some of the most common pitfalls include:

– A goal that is not well enough defined

– No clear plan for how to use the final result

– Incorrect allocation of resources

– Insufficient data quality checks

– Under-estimating the importance of labels

– Lack of understanding of the limitations of different approaches

– Overly-optimistic time estimates

– Failure to account for the iterative nature of machine learning

– No plan for how to evaluate the success of the project

Wanna know how not to fail at machine learning before you even begin?

So how do you avoid these problems? Where do you start? How do you plan a machine learning project? How do you estimate how long it will take? What resources do you need? What does a machine learning project look like in practice? Why should you even bother? Join us for a webinar where we will talk about scoping and planning machine learning projects. We’ll cover the entire project life cycle and give you our best tips for making your project a success.


Learn more about what it is, and how not to fail in your attempt to create new value with machine learning.
Join our webinar Thursday 15th of April at 10.00-11.00!


Meet your hosts – Gemma and Christian

Gemma Danks – listed as one of Norway’s 50 leading women in tech 2021, she will talk you through the magic of machine learning, joined by our host Christian Sloper.

Gemma Danks

Gemma is a partner and senior consultant in data science and machine learning at Sonat Consulting and was named one of Norway’s leading women in tech in 2021. She specialises in deep learning and develops AI solutions to help our customers solve real-world problems. Gemma has a PhD in complex systems analysis, a research background in genomics, computational biology and bioinformatics, and 15 years of experience in data analysis, programming and machine learning. Along with hiking in the mountains, astrobiology and writing fantasy books for her children, planning is one of Gemma’s favourite pastimes. In the webinar, Gemma will be sharing what she’s learnt about scoping and planning machine learning projects to help you get a better grasp of where to start.

Connect with Gemma on LinkedIn.

Christian Sloper

Christian Sloper is a partner and group leader for data science and machine learning at Sonat Consulting.   Christians focus is on architecture and operalization of data science, it is not enough to just have the data science models, they must be put into use as well. He has a PhD in algorithms and complexity theory and 15 years of experience in data warehousing, data engineering and programming.  In his off hours, Christian likes to be a dad, and wrestle with both number theory and people.

Sonat har i dag 71 ansatte og leverer tjenester innen IT rådgiving, prosjektledelse, maskinlæring, kunstig intelligens, front-end utvikling, back-end utvikling og arkitekturrådgiving. Selskapet er solid og har hatt god og lønnsom vekst gjennom snart 8 år.

Sonat har kontor i Bergen og Oslo.


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