Are you interested in learn more about Google’s deep learning? Google is offering a new course at Udacity “Deep Learning: Taking machine learning to the next level.” They also posted more details on Google’s decision to offer this course here.
To help make deep learning even more accessible to engineers and data scientists at large, we are launching a new Deep Learning Course developed in collaboration with Udacity. This short, intensive course provides you with all the basic tools and vocabulary to get started with deep learning, and walks you through how to use it to address some of the most common machine learning problems. It is also accompanied by interactive TensorFlow notebooks that directly mirror and implement the concepts introduced in the lectures.
The course itself covers the building blocks of machine learning, designed to help engineers learn more about machine learning, one of many course that Udacity is currently offering on the topic of machine learning for engineers.
We’ll show you how to train and optimize basic neural networks, convolutional neural networks, and long short term memory networks. Complete learning systems in TensorFlow will be introduced via projects and assignments. You will learn to solve new classes of problems that were once thought prohibitively challenging, and come to better appreciate the complex nature of human intelligence as you solve these same problems effortlessly using deep learning methods.
It does have some pretty hefty course prerequisites.
- Minimum 2 years of programming experience (preferably in Python)
- Git and GitHub experience (assignment code is in a GitHub repo)
- Basic machine learning knowledge (especially supervised learning)
- Basic statistics knowledge (mean, variance, standard deviation, etc.)
- Linear algebra (vectors, matrices, etc.)
- Calculus (differentiation, integration, partial derivatives, etc.)
However, as a free course, there could be useful information for those that do not meet the full prerequisites to enroll.
You can find more course information here, as part of the Machine Learning Engineer Nanodegree program.
Jennifer Slegg
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