For the latest developments on AI: https://medium.com/aiguys
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[1] BackPropagation: https://www.nature.com/articles/323533a0
[2] 3Blue1Brown: https://www.youtube.com/watch?v=aircAruvnKk&list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi
[3] AI vs Kasparov: https://www.youtube.com/watch?v=NJarxpYyoFI&ab_channel=Eustake
[4] AI Playing Jeopardy: https://www.youtube.com/results?search_query=AI+plays+Jeopardy
[5] Libratus Poker: https://www.youtube.com/watch?v=jLXPGwJNLHk&ab_channel=Engadget
[6] Alpha GO paper: https://www.nature.com/articles/nature16961
[7] Open AI Dota paper: https://arxiv.org/abs/1912.06680
[8] Human vs AI in GO part 2: https://goattack.far.ai/pdfs/go_attack_paper.pdf
[9] Anaconda Downloads: https://www.anaconda.com/download/
[10] VS Code Download: https://code.visualstudio.com/download
[11] Installing Git: https://git-scm.com/book/en/v2/Getting-Started-Installing-Git
[12] OOPS in Python: https://www.youtube.com/watch?v=JeznW_7DlB0&ab_channel=TechWithTim
[13] Write Regex expression from english text: https://www.autoregex.xyz/
[14] NN as Universal Approximators: https://ieeexplore.ieee.org/document/256500
[15] Paper on Neural Network pruning: https://arxiv.org/abs/2103.06460
[16] GATO: A generalised agent paper: https://arxiv.org/pdf/2205.06175.pdf
[17] StatsQuest video on PCA: https://www.youtube.com/watch?v=FgakZw6K1QQ&ab_channel=StatQuestwithJoshStarmer
[18] Understanding SMO, similar to SGD optimization: https://en.wikipedia.org/wiki/Sequential_minimal_optimization
[19] Optimization of Logistic regression: https://medium.com/aiguys/beautiful-maths-behind-logistic-regression-optimization-6cefd3ec1c91
####ERRORS:
Page 134: Let’s talk about the preceding optimization problem; it’s an optimization problem where we are trying to minimize (weights and biases) such that alphas are maximized. It’s a MIN(MAX) problem where we are trying to minimize the product of W(transpose) and W such that Y_k [WTX_k + b] >= 1.
[21] 3Blue1Brown Backpropagation video: https://www.youtube.com/watch?v=Ilg3gGewQ5U&ab_channel=3Blue1Brown
[22] Different pooling methods paper: https://arxiv.org/ftp/arxiv/papers/2009/2009.07485.pdf
[23] Stanford CNN video lecture: https://www.youtube.com/watch?v=bNb2fEVKeEo&list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv&index=5&ab_channel=StanfordUniversitySchoolofEngineering
[24] Stanford CNN architectures: https://www.youtube.com/watch?v=DAOcjicFr1Y&list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv&index=9&ab_channel=StanfordUniversitySchoolofEngineering
[25] TensorFlow Guide: https://www.tensorflow.org/guide/
[26] Weights and Biases tutorials: https://docs.wandb.ai/tutorials
[27] IIIT Pet dataset: https://www.robots.ox.ac.uk/~vgg/data/pets/
[28] Stanford RNN lecture: https://www.youtube.com/watch?v=6niqTuYFZLQ&ab_channel=StanfordUniversitySchoolofEngineering
[29] Statsquest video on LSTM: https://www.youtube.com/watch?v=YCzL96nL7j0&ab_channel=StatQuestwithJoshStarmer
[30] MIT: Transformer, and Attention: https://www.youtube.com/watch?v=ySEx_Bqxvvo&ab_channel=AlexanderAmini
[31] Stanford, self-attention and transformers: https://www.youtube.com/watch?v=ptuGllU5SQQ&ab_channel=StanfordOnline
[32] VAE explained: https://www.youtube.com/watch?v=9zKuYvjFFS8&t=530s&ab_channel=ArxivInsights
[33] Power of GANs: https://this-person-does-not-exist.com/en
[34] Stanford: Generative models: https://www.youtube.com/watch?v=5WoItGTWV54&ab_channel=StanfordUniversitySchoolofEngineering
[35] Ian Goodfellow on GANs: https://www.youtube.com/watch?v=Z6rxFNMGdn0&t=656s&ab_channel=LexFridman