What are the best ways to stay motivated while building a machine learning portfolio?

Start small and don't be in a haste. That's the best thing to do. Just have fun along the way and document it as you grow. It might take a lot of time but it'll be worth it trust me.

example of how to set a realistic goal: Instead of saying, "I want to build a portfolio of 10 ML projects," say, "I want to build a portfolio of 2 ML projects in the next 6 months." This goal is more specific, measurable, achievable, relevant, and time-bound. You could create a list like this: Month 1: Learn about the basics of ML and choose two projects to work on. Month 2: Collect and prepare data for the first project. Month 3: Train and evaluate the first ML model. Month 4: Deploy the first ML model and write a blog post about the project. Month 5: Collect and prepare data for the second project. Month 6: Train and evaluate the second ML model. Month 7: Deploy the second ML model and write a blog post about the project.

Setting realistic goals is the cornerstone of maintaining motivation, particularly in the challenging arena of ML. It's important to align these goals with your current capabilities while ensuring they stretch your abilities without overwhelming you. Celebrating small milestones not only fuels drive but also provides opportunities for reflection and course correction. A structured approach to goal setting, complemented by periodic reviews, enables a sustainable pace, and keeps the flame of motivation steadily burning.

Sometimes you want to get into the hard stuff: NLP and Computer Vision yet you're struggling with pandas. This shouldn't be so. You can start with simple EDA projects, some visualizations, basic ML before tackling the big guns.

A highly effective method for testing projects and approaches, while setting realistic goals, is to participate in relevant hackathons. These events offer excellent opportunities to create initial yet functional prototypes of projects, engage in fun, and tackle challenges. I've discovered that LabLab.AI hosts accessible hackathons that are easy to participate in, though it's likely there are also organizations near you or aligned with your interests.

This can be really helpful. Getting an internship, a mentor, or some community would really help. You get to learn from other people and you'll have others to guide and comfort you(You'll get frustrated at some point believe me)

Never stop learning. You can revisit that old python course, check out the latest on blogs or YouTube, pay for a course. Whatever it is you do, never stop learning. You can take a break once in awhile though, after all we're only human.

Continuous learning is a driving force in maintaining motivation, especially in machine learning. The pursuit of knowledge is an endless journey; there's always a new algorithm to master, a novel application to explore, or a complex problem to solve. This constant learning curve is not a hurdle but a catalyst that keeps the mind actively engaged and continuously evolving. Embracing a growth mindset opens the door to perpetual improvement, ensuring that the process of building your portfolio itself becomes a rewarding educational experience. The quest for knowledge, if nurtured properly, becomes a self-perpetuating cycle of motivation.

Having fun developing a project kind of makes it look easier. It eases the tension. You could start a project and let your friends contribute. Either way, you will all have fun whilst learning from one another.