Programming languages have always evolved, but the most significant achievement in this area has been the simplification of working with code. Now instead of writing codes, you configure your computer to learn by itself. This process was called Machine Learning and it consists in a set of methods and algorithms which analyze the available information and learn to recognize images, identify behavior patterns and find compliance with these patterns.
This technology promises to be a real breakthrough that can affect any person ro business, regardless of the scope of their activity. Fortune Business Insights state that the global Machine Learning market is expected to grow from $21.17 billion in 2022 to $209.91 billion by 2029, at a CAGR of 38.8%.
As ML and AI initiatives are becoming more widespread, organizations embed the technologies to boost company growth in a wider spectrum of directions. In this way, we see optimized processes of the companies’ workflows, including:
- Personalized product recommendations;
- Reduced equipment downtime;
- Improved employee productivity;
- Customer lifetime value predictions;
- Trend and demand forecast;
- Data-informed decision-making;
- Increased operational efficiencies and more
Why You Need a Machine Learning Consultant?
As data complexity increases, ML solutions need to address ever-changing realities. However, designing and implementing these large systems require expert guidance from specialists in the field.
“Successful ML project is completed only when the right questions are asked – and answered – in advance. Without proper planning, the chances for failure considerably overweigh.”
For this reason, most providers of Machine Learning solutions offer consulting services to help clients build and implement custom deep learning solutions for their products and services.
But how to choose a reliable Machine Learning consulting company that is aimed at achieving the best results possible? In this article, we’ve pointed out 6 factors to keep an eye on:
1. Study The Portfolio
Be sure to check the portfolio of the Machine Learning consulting firm you choose. Look at the number, complexity, and variety of their works. Preferably, the company should have experience in projects similar to yours. If your views don’t coincide in many ways or you don’t like their works, look for some other team.
2. Look for Published Technical Expertise
When it comes to selecting consulting services, skills and processes are equally as important as technology choices. Consultants are generally considered intelligent people with profound insights into the domain they specialize in. Such people have the potential and should create educational content that enlightens their followers with knowledge on a specific subject – in our case, Machine Learning. An expert ML consulting firm regularly publishes white papers, informative articles, and concise case studies on Machine Learning, which shows their deep expertise.
3. Verify Consultants’ Qualifications
Besides theoretical knowledge of ML and AI, building projects in the given subject area necessitates a set of related skills and competencies. The top must-have skills include Machine Learning, Python, collaboration, statistics, innovation skills, and critical thinking. In addition, a trustworthy consultant is well-versed in ML libraries and frameworks and knows firsthand what a data-driven project looks like.
4. Check Out Customers’ Feedback
This is one of the obvious aspects, although usually taken with suspicion. Many clients often overlook a consultancy firm’s reviews, as they may be purchased or written by an agency's marketing manager. Reviews can say a lot but it is better to evaluate reviews on independent sites or watch video reviews if there are any.
If you wish, you can contact a company’s former clients and find out the intricacies of working with the consultants: their communication skills, the viability of their solutions, and more.
5. Interview A Consulting Company
Once you shortlisted a number of consulting firms, it’s time to contact each and see who will be the best match for your company’s goals and needs. The evaluation phase is the foundation of any project. This is where a consultant helps you frame your problem, find a feasible solution, and define the project scope and the results. At this step, the ratio of investment to profits is calculated as well.
Consider hiring data science consultant teams that play a fair game in evaluating your solution options, their cost and value in terms of ROI.
6. Pay Attention to The Questions You’re Asked
An expert consultant knows what questions to ask to dig to the heart of the issue. Their first and foremost priority is not to sell services but to understand and solve your problem. Having asked the right questions at the beginning, experienced consultants can say whether the project is viable from the outset. This will let off the pressure and help evade costly misunderstandings and fixes afterward.
Conclusion
Machine Learning is helping us conquer new heights in all industries. Yet one thing remains constant: the need to sensibly analyze opportunities, manage the algorithms, and deliver the results in a comprehensive and gainful way. Only when wisely thought out and correctly deployed by a vetted team, Machine Learning can yield impactful insights and bottom-line results.
