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Aspiring ML Engineer? 8 Tips You Need To Know

AI is changing the world. How can you take part?

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There's never been a more exciting time to be an engineer, let alone one focused on machine learning and artificial intelligence. As technology becomes increasingly advanced and computers become smaller, faster, and more efficient, the opportunities for engineers are expanding exponentially.

Machine learning is popular for a reason. It's a field that's providing new solutions to difficult problems, answers that have eluded humans for some time. It's one of the most important computer science disciplines and it's only going to grow in importance as time goes on. Getting involved in machine learning now means that engineers can shape the future of AI as we know it. The ability to be a part of the future, be involved in cool use cases, and push the cutting edge of tech is what makes this role exciting. If you want to be involved in the action of machine learning and AI, we are here to help!

Getting Started with Machine Learning

1. Interest Is Always The Best Teacher

Ayush Chaurasia is a Machine Learning engineer here at Ultralytics. The key to sparking his interest in ML was actually music. When he was in high school, he specifically wanted to build a smart recommender for his media player because it was too boring to listen to the same songs every day.While Ayush never completed the project, he continued exploring the world of ML research. Since then, he's been working on interesting ML solutions for real-world problems.

2. It Is Not About Being Smart, It is About Being Stubborn

Sometimes, people might think that one has to be an Einstein to get involved in this industry, but it’s actually not the case. At the end of the day, it’s all about persistence and believing that you’re going to solve every problem in front of you. The world of Artificial Intelligence is extremely complex, but a good ML engineer doesn’t shy away from challenges.

3. Broaden Your Horizons, Get The Basics Right

ML continues to be a very new field, with all sorts of different research papers and reports appearing every day. It’s easy to get caught up in the latest paper and forget about your original goal. Make sure you are doing what you can, not just chasing papers!

4. Learn Python

Before you can jump into the world of machine learning, it's crucial to know how to program computers. Python will teach you how to think algorithmically so that you can react quickly in a dynamic world where everything changes at light speed. It’s also one of the most popular languages for machine learning, with many tools built on top of it including YOLOv5.

5. Understand Supervised ML Techniques

Supervised machine learning techniques include regression, association, and classification. The understanding of those will enable you to set up an appropriate structure for your own data, be able to use appropriate tools by understanding the main options available, and make informed choices about appropriate algorithms and hyperparameters.

6. Good Tools At Your Disposal

Tools such as Google Colab, Pytorch, and Pycharm are very useful and helpful, Google Colab is GPU Free, PyTorch is a popular deep learning framework and PyCharm is an IDE that provides rich tooling support within the interface. With these tools, you will be able to improve your productivity and develop your dialectical thinking skills.

7. Start Building Projects As Soon As Possible

The earlier you start building your own projects, the higher your chances of success. Be prepared to make mistakes, be prepared to fail, and get back up again. Learning from your own mistakes is the fastest way to grow. It's the toughest, but most rewarding path.

8. Ready For Both Excitements and Challenges

Machine Learning is a fast-moving industry where ideas that came up two years ago are now in production. You'll always feel excited, especially when your solutions are useful and you know you're making contributions to the world.However, there will be challenges. Lack of resources and time, large processing power, and necessary hardware improvements are just some examples. You should remember to always be patient and embrace both the ups and downs.

Inspiration From Glenn

Just a few years ago, our founder, Glenn Jocher, started in AI and ML as an outsider coming from a background in physics. Keeping this in mind, Glenn’s success did not happen overnight. It took patience and determination. YOLOv5 started out as a humble idea. By working hard, we built a team. Everything we offer is open-source, as we aim to make AI easy and accessible to everyone.

“If you want to enter the world of machine learning, I hope you will always keep your heart, be humble, patient, and determined in pursuing your dreams!”
Founder & CEO of Ultralytics, Glenn Jocher

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