Here are 5 passive income ideas for developers👨🏻💻 -
1. Build and Sell Apps or Plugins 🛠️📱
Create a simple app, browser extension, or WordPress plugin. Publish it, set a price, and let the downloads roll in! 💵
2. Launch an Online Course 🎓💻
Share your coding wisdom! Record tutorials on platforms like Udemy or Gumroad, and earn every time someone enrolls. 📚✨
3. Develop SaaS Products ☁️🚀
Solve a niche problem with a subscription-based software service. Think task trackers, productivity tools, or analytics dashboards! 💡💰
4. Write a Tech Ebook 📖👨💻
Document your expertise in a programming language or framework. Publish it on Amazon or Leanpub and watch the royalties stack up. 📘💸
5. Create a YouTube Channel 📹💻
Share coding tutorials, dev tips, or even live coding sessions. Once you get enough views and subscribers, YouTube ads, sponsorships, and memberships can bring in steady income! 🎬💰
1. Build and Sell Apps or Plugins 🛠️📱
Create a simple app, browser extension, or WordPress plugin. Publish it, set a price, and let the downloads roll in! 💵
2. Launch an Online Course 🎓💻
Share your coding wisdom! Record tutorials on platforms like Udemy or Gumroad, and earn every time someone enrolls. 📚✨
3. Develop SaaS Products ☁️🚀
Solve a niche problem with a subscription-based software service. Think task trackers, productivity tools, or analytics dashboards! 💡💰
4. Write a Tech Ebook 📖👨💻
Document your expertise in a programming language or framework. Publish it on Amazon or Leanpub and watch the royalties stack up. 📘💸
5. Create a YouTube Channel 📹💻
Share coding tutorials, dev tips, or even live coding sessions. Once you get enough views and subscribers, YouTube ads, sponsorships, and memberships can bring in steady income! 🎬💰
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To become a Machine Learning Engineer:
• Python
• numpy, pandas, matplotlib, Scikit-Learn
• TensorFlow or PyTorch
• Jupyter, Colab
• Analysis > Code
• 99%: Foundational algorithms
• 1%: Other algorithms
• Solve problems ← This is key
• Teaching = 2 × Learning
• Have fun!
• Python
• numpy, pandas, matplotlib, Scikit-Learn
• TensorFlow or PyTorch
• Jupyter, Colab
• Analysis > Code
• 99%: Foundational algorithms
• 1%: Other algorithms
• Solve problems ← This is key
• Teaching = 2 × Learning
• Have fun!
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The Statistics and Machine Learning with R Workshop.pdf
25.7 MB
The Statistics and Machine Learning with R Workshop
Liu Peng, 2023
Liu Peng, 2023
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2301.04856.pdf
39.1 MB
Multimodal Deep Learning
This book is the result of a seminar in which we reviewed multimodal approaches and attempted to create a solid overview of the field, starting with the current state-of-the-art approaches in the two subfields of Deep Learning individually.
This book is the result of a seminar in which we reviewed multimodal approaches and attempted to create a solid overview of the field, starting with the current state-of-the-art approaches in the two subfields of Deep Learning individually.
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