How can a product team that has no experience with ML start using it?
Yaro Lozhkin
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I wonder if an established product that has little proprietary data for training a ML model (e.g., niche B2B products, development tools with 100-1000 customers) could benefit from an AI.
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Hemant Warier@hemantwarier
Notesally 2.0
As a product team that has no experience with machine learning (ML), it can be daunting to start incorporating it into your work. However, there are a few steps you can take to begin incorporating ML into your product development process.
1. Identify the problem you want to solve: Start by identifying the problem you want to solve using ML. This could be anything from improving customer engagement to increasing conversion rates. Once you have identified the problem, you can start to research the different ML techniques that can help you solve it.
2. Learn about ML basics: Before diving into specific ML techniques, it's important to understand the basics of machine learning. This includes understanding the different types of ML algorithms, how they work, and the data they require. You can do this by reading introductory ML books or taking online courses.
3. Get your team involved: ML is a team effort, and it's important to get your entire team involved in the process. This includes developers, data scientists, and product managers. By working together, you can ensure that everyone is on the same page and that the team is able to move forward with the project.
4. Start small: When starting out with ML, it's important to start small. This means focusing on a specific problem and using a simple ML algorithm to solve it. This will allow you to get a feel for how the process works and will help you identify any potential challenges.
5. Partner with experts: If your team is still new to ML, it may be helpful to partner with experts who can guide you through the process. This could include working with a data science consultant or a ML-focused startup. By partnering with experts, you can ensure that your team is using the right techniques and that the project is moving in the right direction.
In summary, starting with ML can be daunting, but by identifying the problem, understanding the basics of ML, getting your team involved, starting small, and partnering with experts, you can begin incorporating ML into your product development process and ultimately reap the benefits of this technology.
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