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In this episode, we have Thomas J Fan sharing how his open source contributions and physics background paved the way for his successful transition into a machine learning career --- SUBSCRIBE TO OUR NEWSLETTER TO RECEIVE: 🚀 Episode Summaries: Get the latest episode in a digestible format 💡 Coding Tips & Tricks: Level up your skills with practical advice from industry experts. 🔮 Tech Trends: Stay ahead of the curve with our curated digest of emerging technologies. 🎁 Special Offers: Be the first to know about upcoming events, courses, and podcast merchandise. 👥 Community Spotlights: Connect with fellow coders and see what our listeners are building. ✉️ https://newsletter-signup-form-cf0560... WANT TO SHARE YOUR TECH JOURNEY? 📒 https://forms.gle/jD8QMJKCMux7y82E9 --- Follow Culture of Code 💬 Discord - / discord 📄 LinkedIn Page - / 102845596 🐦 Twitter - / felixthea 🎤 Apple Podcast - https://podcasts.apple.com/ie/podcast... 🎧 Spotify - https://open.spotify.com/show/0fqIsZc... Timestamps 0:00 🤝Meet Thomas 01:19 🚀 Transition from Software Engineer to Machine Learning Engineer 02:48 🛤️ Steps to Becoming a Machine Learning Engineer 03:42 🔍 Differences Between Data Engineers and Machine Learning Engineers 04:25 🌐 Connecting Machine Learning to Domain Expertise 04:53 💻 Breaking into Software Engineering Through Open Source 05:51 🌟 Benefits of Open Source Contributions 07:29 🏁 Getting Started with Open Source Projects 08:40 📚 Recommended Open Source Communities for Machine Learning 09:31 📈 Leveraging Open Source Contributions in Job Searches 14:23 🎤 Preparing for Tech Talks 15:22 📄 Reframing Your Resume for Tech Roles 16:35 📝 Machine Learning Engineer Interview Process 17:37 🌟 Future Opportunities in Machine Learning #artificialintelligence #machinelearning #techcareers