Train your own AI using this free Lab created by Dr Mike Pound.
Big thanks to Brilliant for sponsoring this video! Get started with a free 30 day trial and 20% discount: https://brilliant.org/DavidBombal

How do you capitalize on this trend and learn AI? Dr Mike Pound of Computerphile fame shows us practically how to train your own AI. And the great news is that he has shared his Google colab lab with us to you can start learning for free! If you are into cybersecurity or any other tech field, you probably want to learn about AI and ML. They can really help your resume and help you increase the $$$ you earn.

Machine Learning / Artificial Intelligence is a fantastic opportunity for you to get a better job. Start learning this amazing technology today and start learning with one of the best!

// MENU //
00:00 - Intro
00:41 - Sponsored segment
01:37 - Detectron 2 tutorial walkthrough // Learning object detection
05:39 - Multi-task learning example // Detecting plants
08:07 - Multi-task learning walkthrough and demo
19:24 - Learning Python for AI // Andrew Ng's machine learning course
20:47 - Many uses of object detection
21:38 - Detectron 2 on RaspBerry Pi
23:26 - PyTorch Examples
24:20 - "Start with the simple things"
25:00 - How ChatGPT is making people interested in AI
27:15 - Great time to get into AI
27:31 - Is it too late to get into AI?
28:19 - Conclusion

// LAB //
Go here to access the lab: https://colab.research.google.com/drive/15oFpx_u6Cj24Dkbr7lARTYaN8MXcr8fy?usp=sharing

// Previous Videos //
Roadmap to ChatGPT and AI mastery: https://youtu.be/evN89fdKOxU
I challenged ChatGPT to code and hack: https://youtu.be/Fw5ybNwwSbg
The truth about AI and why you should learn it - Computerphile explains: https://youtu.be/PH9RQ6Yx75c

// Dr Mike's recommend AI Book //
Deep learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville: https://amzn.to/3vmu4LP

// Dawid's recommend Books //
1. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: https://amzn.to/3IrGCHi
2. Pattern Recognition and Machine Learning: https://amzn.to/3IWVm2v
3. Machine Learning: A Probabilistic Perspective: https://amzn.to/3xYFM05
4. Python Machine Learning: https://amzn.to/3y0r08Q
5. Deep Learning: https://amzn.to/3kxSbVu
6. The Elements of Statistical Learning: https://amzn.to/3Iwuuox
7. Linear Algebra and Its Applications: https://amzn.to/3EGwMAs
8. Probability Theory: https://amzn.to/3IrGeZm
9. Calculus: Early Transcendentals: https://amzn.to/3Z3Eugh
10. Discrete Mathematics with Applications: https://amzn.to/3Zpzpyt
11. Mathematics for Machine Learning: https://amzn.to/3m8jp5N
12. A Hands-On Introduction to Data Science: https://amzn.to/3Szob8c
13. Introduction to Algorithms: https://amzn.to/3xXo50K
14. Artificial Intelligence: https://amzn.to/3Z2fqGv

// Courses and tutorials //
AI For Everyone by Andrew Ng: https://www.coursera.org/learn/ai-for-everyone
PyTorch Tutorial From Research to Production:
https://www.infoq.com/presentations/pytorch-torchscript-botorch/
Scikit-learn Machine Learning in Python:
https://scikit-learn.org/stable/

// PyTorch //
Github: https://github.com/pytorch
Website: https://pytorch.org/
Documentation: https://ai.facebook.com/tools/pytorch/

// Mike SOCIAL //
Twitter: https://twitter.com/_mikepound
YouTube: https://www.youtube.com/user/Computerphile
Website: https://www.nottingham.ac.uk/research/beacons-of-excellence/future-food/meet-the-team/michael-pound/index.aspx

// David SOCIAL //
Discord: https://discord.com/invite/usKSyzb
Twitter: https://www.twitter.com/davidbombal
Instagram: https://www.instagram.com/davidbombal
LinkedIn: https://www.linkedin.com/in/davidbombal
Facebook: https://www.facebook.com/davidbombal.co
TikTok: http://tiktok.com/@davidbombal
YouTube: https://www.youtube.com/davidbombal

// MY STUFF //
https://www.amazon.com/shop/davidbombal

// SPONSORS //
Interested in sponsoring my videos? Reach out to my team here: [email protected]

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python
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ai lab
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Please note that links listed may be affiliate links and provide me with a small percentage/kickback should you use them to purchase any of the items listed or recommended. Thank you for supporting me and this channel!

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