## Lecture 16.3 — Bayesian optimization of hyper-parameters [Neural Networks for Machine Learning]

Lecture from the course Neural Networks for Machine Learning, as taught by Geoffrey Hinton (University…

Lecture from the course Neural Networks for Machine Learning, as taught by Geoffrey Hinton (University…

Lecture from the course Neural Networks for Machine Learning, as taught by Geoffrey Hinton (University…

A Gentle Introduction to Boosting Machine Learning Algorithms If you do have any questions with…

An updated deep learning introduction using Python, TensorFlow, and Keras. Text-tutorial and notes: https://pythonprogramming.net/introduction-deep-learning-python-tensorflow-keras/ TensorFlow…

( TensorFlow Training – https://www.edureka.co/ai-deep-learning-with-tensorflow ) This Edureka “Neural Network Tutorial” video (Blog: https://goo.gl/4zxMfU) will…

In this talk, Danny Yuan explains intuitively fast Fourier transformation and recurrent neural network. He…

In this video, we explain the concept of unsupervised learning. We also discuss applications of…