Free

Intro to TensorFlow for Deep Learning

Course

Dive into deep learning with this practical course on TensorFlow and the Keras API. Gain an intuitive understanding of neural networks without the dense jargon. Learn to build, train, and optimize your own networks using TensorFlow. The course also introduces transfer learning, leveraging pre-trained models for enhanced performance. Designed for swift proficiency, this course prioritizes hands-on learning and real-world applications.

Built in collaboration with

Google

Last Updated September 25, 2023

Prerequisites:

No experience required

Course Lessons

Lesson 1

Welcome to the Course

Welcome to the course! Say hello to your instructors and get an overview of the program.

Lesson 2

Introduction to Machine Learning

Build your first neural neural network and learn some of the basic concepts behind machine learning.

Lesson 3

Your First Model - Fashion MNIST

Create and train a neural network that can recognize images of articles of clothing.

Lesson 4

Introduction to CNNs

Create and train a convolutional neural network that can recognize images of articles of clothing.

Lesson 5

Going Further With CNNs

Let's dive deeper into the further complexities of Convolutional Neural Networks!

Lesson 6

Transfer Learning

Find out how transfer learning can greatly speed up your training process, allowing you to use existing networks as a basis for your own.

Lesson 7

Saving and Loading Models

Learn how to save and load your trained models.

Lesson 8

Time Series Forecasting

Learn how to perform time series forecasting using deep learning and TensorFlow.

Lesson 9

NLP: Tokenization and Embeddings

Get introduced to Natural Language Processing with TensorFlow by learning how to tokenize words and create embeddings for use in neural networks.

Lesson 10

NLP: Recurrent Neural Networks

Climb further with your NLP skills by building recurrent neural networks in TensorFlow, as well as learning how to generate new text for areas like song lyrics.

Lesson 11

Introduction to TensorFlow Lite

Learn how to deploy your models on Android, iOS, and IoT devices using TensorFlow Lite.

Taught By The Best

Magnus Hyttsten

Engineering Manager at Google

Magnus is the founder of DigitalRoute and has been working at Google in since 2013, as engineering manager and individual contributor for a variety of software products.

Juan Delgado

Content Developer

Juan is a computational physicist with a Masters in Astronomy. He is finishing his PhD in Biophysics. He previously worked at NASA developing space instruments and writing software to analyze large amounts of scientific data using machine learning techniques.

Paige Bailey

Developer Advocate, Google

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Demonstrate proficiency with practical projects

Projects are based on real-world scenarios and challenges, allowing you to apply the skills you learn to practical situations, while giving you real hands-on experience.

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Reviewers provide timely and constructive feedback on your project submissions, highlighting areas of improvement and offering practical tips to enhance your work.