Data science and machine learning projects can quickly transform into 6- or 7-figure investments.
But planning, staffing and executing cutting-edge projects and working out what you’ll get in return for your investment can be tricky.
Are planning a major new analytics endeavour
Need to know the best ways to plan, manage, and secure machine learning projects
And need your project done right the first time
I can help.
The Machine Learning Roadmap is a four stage consulting engagement that transfers the experience and skills I’ve developed over a decade in data analytics and machine learning. You and your team will discover:
Stage One: Audit
You’ll discover where your organisation should start with machine learning.
The most common questions I’m asked by business considering a major new analytics project are all about their readiness. Do we have the infrastructure we need? Do we have the data? Do we have the people?
The audit stage allows us to find out where your company is on the way to machine learning success. It’s an in-depth analysis of the processes, systems, infrastructure, and people in the organisation which serves as a baseline for the rest of the engagement.
Stage Two: Training
Machine learning is filled with jargon and complex ideas. Even highly-technical CTOs can feel as though they’re out of the loop when it comes to data science and ML.
The training stage gives us the opportunity to develop everyone’s understanding of how machine learning works and how it can change products, services and businesses, too.
It’s an essential step in preparing for a successful, collaborative machine learning project.
Stage Three: Staffing
Despite what most data scientists would have you believe, nobody can do everything.
The staffing stage allows you to get a feel for who you need to hire to make the project a success. It will also highlight how machine learning talent can be developed in your current team.
At the end of this stage everyone will have developed their understanding of the skills it takes to build, deploy and maintain large-scale analytics projects.
Stage Four: Planning
What are the key stages of a machine learning project? How will we take an idea or a problem and turn it into a working solution that benefits the business?
The planning stage will highlight the specific milestones and pitfalls that you’ll encounter while making your machine learning project a reality. It will move step-by-step from the systems that generate the raw data, right through to where the predictions will end up.
This is the stage that helps get buy-in from senior stakeholders, as risks and rewards are clearly laid out by someone who’s been there before.
To really get to know your business and your people, I’ll need to schedule meetings with key stakeholders over the course of several weeks (between 5 and 7 hours of meetings).
We’ll run exploration exercises, I’ll teach your team the basics of machine learning (from junior engineers up to executives), and I’ll be on hand to answer any pressing questions.
Each deliverable will be presented to the relevant stakeholders and I’ll work closely with your team to ensure they understand how to put our findings into practice.
If you need any help after this, I’ll just be a phone call away.
Hi, I’m Carl Dawson and I have been working in analytics and data science for over a decade, helping world-leading brands and startups discover, strategise, and deliver projects with machine learning at their core.
I created the Machine Learning Roadmap to help companies (like yours) explore how data science and machine learning can transform their business while mitigating the risk involved in such a high-cost endeavour.
I write frequently for FreeCodeCamp, The Startup and Towards Data Science and I am a graduate of the University of Oxford.
Are you having problems with a pre-existing project? Perhaps you need an expert on call to help you solve problems and make decisions?
If you’re already working with machine learning at scale but need someone to help ensure you keep progressing, get in touch to find out about my advisory offerings.
In addition to the Roadmap, I work on a retainer basis for a select number of clients – advising on everything from infrastructure to the latest research.
If you think this may be for you, please request a call and let me know a little about what you’re working on.
WITH CARL’S HELP WE WERE ABLE TO IMPLEMENT A PRODUCTION READY, PROOF-OF-CONCEPT THAT WAS CRUCIAL IN GETTING MY EXECUTIVE TEAM EXCITED ABOUT THE POSSIBILITIES OF MACHINE LEARNING.
CARL IS EXTREMELY KNOWLEDGABLE. HIS METHODS HELPED US DEVELOP AND DELIVER A SOLUTION IN A TIMELY MANNER.
CARL HAS BEEN A PLEASURE TO WORK WITH, KNOWLEDGABLE, PROFICIENT AND EFFECTIVE.