A good Machine Learning strategy is incomplete without leveraging the internal talent that you already have.
SKAI provides hands-on training from the top practitioners and trainers in the field. Our bespoke training courses are highly customized to focus on the specific needs and use-cases of your business. Augmented Labs exercises give your team practical knowledge that can be directly applied back to the problem your team is facing, maximizing the value gained from every session. Our educational programs help you to bridge the gap between technical and business vision, and fully harness the possibilities of Machine Learning and AI.
Every Machine Learning journey starts with a question, so it is important that it is a good question.
Every Machine Learning journey starts with a question, so it is important that it is a good question. It is important to articulate the business problem clearly, narrow down key aims, and assess the available data, in order to produce better overall results for your business.
Prioritising which problem to solve first is the second challenge. While there are many available paths to gain insights for your company, scalable AI works best when adoption is orchestrated and backed by a cohesive strategy.
Machine Learning and AI can’t be tackled with a bolt on mindset. It needs a strategic rollout introduced and guided at the C-suite level and championed across key stakeholders. We will work with you to understand your goals, generate ideas and ensure there is a commercial success story behind your intended projects.
Machine learning is changing the rules.
Businesses are exploring new ways to harness data for extracting real-time business value. In an ever-changing landscape, it can be bit daunting for businesses to identify a right architecture for their business. We can help by assessing your organization’s technical architecture and advise on the most appropriate set of tools. This will reveal opportunities to reduce costs, and increase the accuracy and performance of your systems.
Experimentation and seamless collaboration is the key to a successful Machine Learning or AI project.
We develop a hypothesis about an insight that can be achieved by your data. We then begin developing an MVP (minimum viable product), executing experiments to evaluate assumptions, and iterating accordingly in collaboration with business. The iterative mindset is integral to the discipline of AI and Machine Learning over time. Most of the models are developed on a static subset of data and the conditions might change as new datasets are generated or collected.