Search Results for "basic"

...It provides source code, notebooks, and presentation materials for a practical video-based learning path. The lessons begin with PyTorch setup, tensors, indexing, mathematical operations, gradients, and basic optimization. They then move into neural networks, logistic regression, multilayer perceptrons, CNNs, ResNet, RNNs, LSTMs, autoencoders, VAEs, GANs, graph convolutional networks, and transfer learning. The repository is designed for learners who want to connect deep learning concepts with executable examples. Overall, it is a structured PyTorch practice resource for beginners and early deep learning practitioners.

distribution-is-all-you-need is a Python-based probability tutorial aimed at deep learning researchers and students. It explains common discrete and continuous distributions through short scripts, formulas, descriptions, and plotted graphs. Covered topics include uniform, Bernoulli, binomial, categorical, multinomial, beta, Dirichlet, gamma, exponential, Gaussian, normal, chi-squared, and Student's t distributions. The material highlights relationships such as conjugate priors and...