He gave us all the links and was even nice enough to organize them through slide:

Here is a link to my PPT if anyone in the audience wants a copy. Here are also all the URLs in my deck that can be added to the YT description.

Deck: https://www.dropbox.com/s/vxih5casvo04rrl/vBB%20Laser%20Guided%20Cat%20Bot%202022-03-30.pptx?dl=0 Cat Bot Blog Post: Laser-Guided Autonomous Cat Bot | IT in Context (faucher.net) http://blog.faucher.net/2020/01/laser-guided-autonomous-cat-bot.html

Slide 2: https://jetbot.org/master/getting_started.html https://github.com/dusty-nv/jetson-inference https://colab.research.google.com/#scrollTo=P-H6Lw1vyNNd https://www.kaggle.com/paoloripamonti/twitter-sentiment-analysis Darknet: Open Source Neural Networks in C (pjreddie.com) https://pjreddie.com/darknet/

Slide 5: https://github.com/NVIDIA-AI-IOT/jetbot/blob/master/notebooks/collision_avoidance/live_demo.ipynb Third Person High Res CatBot - YouTube https://www.youtube.com/watch?v=aO1Ur3doiE4&t=7s

Slide 6: NVIDIA: https://github.com/dusty-nv/jetson-inference Google Colab: Tensorflow for Beginners: https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/quickstart/beginner.ipynb Darknet: Darknet: Open Source Neural Networks in C (pjreddie.com) https://pjreddie.com/darknet/ Kaggle: https://www.kaggle.com/paoloripamonti/twitter-sentiment-analysis

Slide 7: https://towardsdatascience.com/clearing-the-confusion-ai-vs-machine-learning-vs-deep-learning-differences-fce69b21d5eb

Slide 8: TensorFlow Tutorial for Beginners: Your Gateway to Building Machine Learning Models (simplilearn.com) TensorFlow Hidden Layer: Hidden Layer Definition | DeepAI How does a Neural Network learn? https://www.kdnuggets.com/2015/12/how-do-neural-networks-learn.html

Slide 9: https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/quickstart/beginner.ipynb

Slide 10: Image Retraining (TF2) https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/tf2_image_retraining.ipynb

Slide 11: Darknet: Open Source Neural Networks in C (pjreddie.com) https://pjreddie.com/darknet/ ./darknet detect cfg/yolov3.cfg yolov3.weights times_square.jpg Train a custom classifier Train a Classifier on CIFAR-10 (pjreddie.com) https://pjreddie.com/darknet/train-cifar/

Slide 12: CIFAR-10 and CIFAR-100 datasets (toronto.edu) https://www.cs.toronto.edu/~kriz/cifar.html Slide 13: Chickens Recognized by Name (While Eating Spaghetti) - YouTube https://www.youtube.com/watch?v=jHzRhhJoYQY&t=65s Slide 14: Cloud AutoML Custom Machine Learning Models | Google Cloud https://cloud.google.com/automl