In 2016, Udacity released the very first free course on TensorFlow in collaboration with Google. Since then, over 400,000 students have enrolled in the course and joined the AI revolution. We’re excited to release an all-new version of this free course featuring the just-announced alpha release of TensorFlow 2.0: Intro to TensorFlow for Deep Learning. This update makes AI even more accessible to everyone, and we’ve again worked directly with the deep learning experts at Google to ensure you’re learning the very latest skills to utilize TensorFlow.
This free course is a practical approach to deep learning for software developers. Our goal is to get you building state-of-the-art AI applications as fast as possible, without requiring a background in math. If you can code, you can build AI with TensorFlow. You’ll get hands-on experience using TensorFlow to implement state-of-the-art image classifiers and other deep learning models. You’ll also learn how to deploy your models to various environments including browsers, phones, and the cloud.
Machine Learning for Everyone
The alpha release of TensorFlow 2.0 is a big milestone for the product. TensorFlow has matured into an entire end-to-end platform. In this alpha release, TensorFlow has been redesigned with a focus on simplicity, developer productivity, and ease of use. This release integrates Keras more tightly into the rest of the TensorFlow platform so that it’s easier for developers new to machine learning to get started with TensorFlow. Along with standardizing around Keras as the main API, other deprecated and redundant APIs have been removed to reduce complexity in the framework. A general release candidate will be available later in Q2 2019.
In order to understand the industry uptake of this emerging technology, we connected with some of our alumni of the Intro to Machine Learning with PyTorch Nanodegree program. Here’s what they said about the impact of the Nanodegree program on their lives.
Update: Applications to this program are now closed. You can access the FREE AWS Deep Racer course here.
Today, we are excited to announce our newest offering to expand students’ machine learning deep learning skills: the DeepRacer Scholarship Challenge from Amazon Web Services (AWS).
This new scholarship program will enable students to acquire skills in machine learning and test their skills in the world’s first autonomous racing league – the AWS DeepRacer League. Top performing students in the DeepRacer League will also have the opportunity to earn their way to a full scholarship to the Machine Learning Nanodegree program with Udacity.
Today, we are excited to announce a new scholarship program with Bertelsmann. Over the next three years, Bertelsmann and Udacity will provide up to 50,000 scholarships in the areas of Cloud Engineering, Data Science and Artificial intelligence. This effort is an expansion of Udacity and Bertelmann’s partnership, as well as, their joint efforts to provide enhanced learning opportunities in emerging technologies.
The program is structured in two phases: In the first phase, 15,000 applicants, per subject area, will be selected to participate in a 3-month Scholarship Challenge phase. In the second phase, the top 5,000 performing Challenge phase students in each subject area will be awarded a full scholarship for a Udacity Nanodegree program.
We have successfully set up and installed a LAMP server on our Ubuntu machine, optimized our server, and now it’s time to learn how to write a Python application – our first one! We won’t be writing anything too fancy, but we will cover the basics of a Python application, and also talk a bit to either our MySQL or PostgreSQL database.
Throughout this tutorial, I will be using the nano editor in the terminal to write my Python code, but feel free to use whichever editor you please. It should not affect the outcome of this tutorial.
Also note that unlike many popular programming languages, Python uses whitespace indentation as a delimiter for code blocks, instead of the traditional curly braces or keywords. This allows Python to have extremely readable code, and forces you not to write single-line functions. Keep this in mind as you are writing your own program, as you don’t want to have issues caused by missing line breaks or indentation.
How to Write a Python Application: Creating Our First .py File
Navigate to a folder that you would like to create your first Python file in, and create a file called test.py. Now open this file up in the editor and type the following code:
“Today I work as a machine learning engineer, it’s like a dream come true,” chuckles the very excited Omkar Sahasrabudhe. Omkar moved from being an intern to a Web Developer and now a Machine Learning Engineer in just a little over a year. This is his story.
Today, we are proud to announce our newest scholarship to expand students’ AI skills: the Intel® Edge AI Scholarship Program.
This new scholarship program, announced at the Intel AI Summit and the Future of Education and Workforce Summit in San Francisco, will empower professional developers interested in advanced learning, specifically deep learning and computer vision, to accelerate the development and deployment of high-performance computer vision and deep learning solutions. Computer vision and AI at the edge are becoming instrumental in powering everything from factory assembly lines and retail inventory management to hospital urgent care medical imaging equipment like X-ray and CAT scans. This program will teach fluency in some of the most cutting-edge technologies.