If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.
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TensorFlow in Practice Specializationdeeplearning.aiAbout this Course
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Learner Career Outcomes
40%
started a new career after completing these courses
43%
got a tangible career benefit from this course
12%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
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Start instantly and learn at your own schedule.
Course 1 of 4 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Experience in Python coding and high school-level math is required. Prior machine learning or deep learning knowledge is helpful but not required.
Approx. 30 hours to complete
English
Subtitles: English, Spanish, Russian, Japanese
What you will learn
Learn best practices for using TensorFlow, a popular open-source machine learning framework
Build a basic neural network in TensorFlow
Train a neural network for a computer vision application
Understand how to use convolutions to improve your neural network
Skills you will gain
Computer VisionTensorflowMachine Learning
Learner Career Outcomes
40%
started a new career after completing these courses
43%
got a tangible career benefit from this course
12%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 1 of 4 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Experience in Python coding and high school-level math is required. Prior machine learning or deep learning knowledge is helpful but not required.
Approx. 30 hours to complete
English
Subtitles: English, Spanish, Russian, Japanese
Offered by
deeplearning.ai
Founded by Andrew Ng, deeplearning.ai is on a mission to make world-class AI education accessible to people around the globe so that we can all benefit from an AI-powered future.
Syllabus - What you will learn from this course
6 hours to complete
A New Programming Paradigm
Welcome to this course on going from Basics to Mastery of TensorFlow. We're excited you're here! In week 1 you'll get a soft introduction to what Machine Learning and Deep Learning are, and how they offer you a new programming paradigm, giving you a new set of tools to open previously unexplored scenarios. All you need to know is some very basic programming skills, and you'll pick the rest up as you go along.
6 hours to complete
4 videos (Total 16 min), 5 readings, 3 quizzes
4 videos
A primer in machine learning3m
The ‘Hello World’ of neural networks5m
Working through ‘Hello World’ in TensorFlow and Python3m
5 readings
Before you begin: TensorFlow 2.0 and this course10m
From rules to data10m
Try it for yourself10m
Introduction to Google Colaboratory10m
Week 1 Resources10m
1 practice exercise
Week 1 Quiz
7 hours to complete
Introduction to Computer Vision
Welcome to week 2 of the course! In week 1 you learned all about how Machine Learning and Deep Learning is a new programming paradigm. This week you’re going to take that to the next level by beginning to solve problems of computer vision with just a few lines of code!
7 hours to complete
7 videos (Total 15 min), 6 readings, 3 quizzes
7 videos
An Introduction to computer vision2m
Writing code to load training data2m
Coding a Computer Vision Neural Network2m
Walk through a Notebook for computer vision3m
Using Callbacks to control training1m
Walk through a notebook with Callbacks1m
6 readings
Exploring how to use data10m
The structure of Fashion MNIST data10m
See how it's done10m
Get hands-on with computer vision1h
See how to implement Callbacks10m
Week 2 Resources10m
1 practice exercise
Week 2 Quiz
8 hours to complete
Enhancing Vision with Convolutional Neural Networks
Welcome to week 3! In week 2 you saw a basic Neural Network for Computer Vision. It did the job nicely, but it was a little naive in its approach. This week we’ll see how to make it better, as discussed by Laurence and Andrew here.
8 hours to complete
6 videos (Total 19 min), 6 readings, 3 quizzes
6 videos
What are convolutions and pooling?2m
Implementing convolutional layers1m
Implementing pooling layers4m
Improving the Fashion classifier with convolutions4m
Walking through convolutions3m
6 readings
Coding convolutions and pooling layers10m
Learn more about convolutions10m
Getting hands-on, your first ConvNet10m
Try it for yourself1h
Experiment with filters and pools1h
Week 3 Resources10m
1 practice exercise
Week 3 Quiz
9 hours to complete
Using Real-world Images
Last week you saw how to improve the results from your deep neural network using convolutions. It was a good start, but the data you used was very basic. What happens when your images are larger, or if the features aren’t always in the same place? Andrew and Laurence discuss this to prepare you for what you’ll learn this week: handling complex images!
9 hours to complete
9 videos (Total 27 min), 10 readings, 3 quizzes
9 videos
Understanding ImageGenerator4m
Defining a ConvNet to use complex images2m
Training the ConvNet with fit_generator2m
Walking through developing a ConvNet2m
Walking through training the ConvNet with fit_generator3m
Adding automatic validation to test accuracy4m
Exploring the impact of compressing images3m
A conversation with Andrew1m
10 readings
Explore an impactful, real-world solution10m
Designing the neural network10m
Train the ConvNet with ImageGenerator10m
Exploring the solution10m
Training the neural network10m
Experiment with the horse or human classifier1h
Get hands-on and use validation30m
Get Hands-on with compacted images30m
Week 4 Resources10m
Wrap up10m
1 practice exercise
Week 4 Quiz
Reviews
TOP REVIEWS FROM INTRODUCTION TO TENSORFLOW FOR ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, AND DEEP LEARNING
by JJApr 27, 2019
Very well organized. Good speakers. Content is comprehensive for a Introductory Course. A little more explanation on Validation versus Testing and on some of the evaluation functions would be helpful.
by ASMar 8, 2019
Good intro course, but google colab assignments need to be improved. And submitting a jupyter notebook was much more easier, why would I want to login to my google account to be a part of this course?
by RDAug 13, 2019
Great course to get started with building Convolutional Neural Networks in Keras for building Image Classifiers. This is probably the best way to get beginners into Deep Learning for Computer Vision.
by ADApr 28, 2020
It is very well designed course,instructors teaches very well,i can understand all concepts and how to solve real problems using using CNN ,want such more projects based on hands on practice ,thanks
About the TensorFlow in Practice Specialization
Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework.
In this four-course Specialization, you’ll explore exciting opportunities for AI applications. Begin by developing an understanding of how to build and train neural networks. Improve a network’s performance using convolutions as you train it to identify real-world images. You’ll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Learn to process text, represent sentences as vectors, and input data to a neural network. You’ll even train an AI to create original poetry!
AI is already transforming industries across the world. After finishing this Specialization, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects.
Looking for more advanced TensorFlow content? Check out the new TensorFlow: Data and Deployment Specialization.
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