Intro to Deep Learning
Arpan Chakraborty and Vincent Vanhoucke via Udacity
- 52
- 12 weeks long
- Udacity
- English
Course Overview
Machine learning is one of the fastest-growing and most exciting fields out there, and deep learning represents its true bleeding edge. In this course, you’ll get an overview of what deep learning is all about.
Partnering with Vincent Vanhoucke, Principal Scientist at Google, and technical lead in the Google Brain team, we’ll teach you how deep learning builds on machine learning. Then you’ll get a chance to learn more about deep neural networks and advanced architectures such as convolutional networks and recurrent networks.
And if you’d like to dive even deeper into this cutting-edge field, we recommend that you continue your studies with our full-fledged Deep Learning Nanodegree program to get more hands-on experience.
Course Circullum
Lesson 1: From Machine Learning to Deep Learning
- Understand the historical context and motivation for Deep Learning.
- Set up a basic supervised classification task and train a black box classifier on it.
- Train a logistic classifier "by hand"Optimize a logistic classifier using gradient descent, SGD, Momentum and AdaGrad.
Lesson 2: Deep Neural Networks
- Train a simple deep network.
- Effectively regularize a simple deep network.
- Train a competitive deep network via model exploration and hyperparameter tuning.
Lesson 3: Convolutional Neural Networks
- Train a simple convolutional neural net.
- Explore the design space for convolutional nets.
Lesson 4: Deep Models for Text and Sequences
- Train a text embedding model.
- Train a LSTM model.
Item Reviews - 3
Submit Reviews
This Course Include:
Lesson 1: From Machine Learning to Deep Learning
- Understand the historical context and motivation for Deep Learning.
- Set up a basic supervised classification task and train a black box classifier on it.
- Train a logistic classifier "by hand"Optimize a logistic classifier using gradient descent, SGD, Momentum and AdaGrad.
Lesson 2: Deep Neural Networks
- Train a simple deep network.
- Effectively regularize a simple deep network.
- Train a competitive deep network via model exploration and hyperparameter tuning.
Lesson 3: Convolutional Neural Networks
- Train a simple convolutional neural net.
- Explore the design space for convolutional nets.
Lesson 4: Deep Models for Text and Sequences
- Train a text embedding model.
- Train a LSTM model.
- Provider:Udacity
- Certificate:Not Avalible
- Language:English
- Duration:12 weeks long
- Language CC: