Lecture 13- Neural Networks - Part I - 2019

Lecture 13: Denoising Images with GANsПодробнее

Lecture 13: Recurrent NetworksПодробнее

Stanford CS229: Machine Learning | Summer 2019 | Lecture 13-Statistical Learning Uniform ConvergenceПодробнее

CS568 Deep Learning, Lecture 13: Backpropagation in Convolutional Neural Networks (Fall 2020)Подробнее

Mathematics for Machine Learning - Lecture 13: Neural Networks III & TensorFlowПодробнее

MIT 6.S192 - Lecture 13: "Surfaces, Objects, Procedures ..." by Jiajun WuПодробнее

Cornell CS 5787: Applied Machine Learning. Lecture 13. Part 1: Boosting and EnsemblingПодробнее

CPSC 330 Lecture 13: neural networks & computer visionПодробнее

(FS 2020) Lecture 13: CNNs for Medical Image Analysis - Part 4Подробнее

MQSS 2019 | L13: Plenary Lecture II | Sean HackettПодробнее

PyTorch Tutorial 13 - Feed-Forward Neural NetworkПодробнее

Lecture 13 (EECS4404E) - Neural Networks (Part IV) - Implementing Neural NetsПодробнее

CS 152—Lecture 13 (HMC Fall, 2019)Подробнее

Lecture 13 | (2/5) Recurrent Neural NetworksПодробнее

Convolutional Neural Networks | Deep Learning in Tamil - Part 13 | #17Подробнее

Lecture 13 – Evaluation Metrics | Stanford CS224U: Natural Language Understanding | Spring 2019Подробнее

Deep Learning Lecture 13: Applying RNN's to Sentiment Analysis (June 2019 update)Подробнее

Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 13 – Contextual Word EmbeddingsПодробнее

Machine Intelligence - Lecture 13 (Convolutional Neural Networks, CNNs)Подробнее

Applied Machine Learning 2019 - Lecture 13 - Parameter Selection and Automatic Machine LearningПодробнее