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 DeepLearning.AI TensorFlow Developer Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
This course is part of DeepLearning.AI TensorFlow Developer Professional Certificate
Instructor: Laurence Moroney
394,546 already enrolled
Gain insight into a topic and learn the fundamentals.
4.8
(19,634 reviews)
Intermediate level
Recommended experience
Flexible schedule
Approx. 22 hours
Learn at your own pace
96%
Most learners liked this course
What you'll 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'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
4 assignments
Taught in English
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This course is part of the DeepLearning.AI TensorFlow Developer Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
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There are 4 modules in this course
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. To get started, check out the first video, a conversation between Andrew and Laurence that sets the theme for what you'll study...
What's included
4 videos8 readings1 assignment1 programming assignment1 app item1 ungraded lab1 plugin
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! Check out this conversation between Laurence and Andrew where they discuss it and introduce you to Computer Vision!
What's included
7 videos3 readings1 assignment1 programming assignment2 ungraded labs
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.
What's included
6 videos3 readings1 assignment1 programming assignment2 ungraded labs
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!
What's included
9 videos6 readings1 assignment1 programming assignment3 ungraded labs
Instructor
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4.8 (4,964 ratings)Offered by
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4.8
19,634 reviews
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Showing 3 of 19634
AS
5
Reviewed on Mar 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?
KS
5
Reviewed on Aug 14, 2020
This course is awesome and the way instructor teaches the topic is fantastic.I would definitely recommend this course for Ai enthusiast and tech enthusiast who are interested in learning Tensorflow.
OO
5
Reviewed on Nov 26, 2020
I give this course 5 stars because of what I'm being able to learn within just a little amount of time. I would highly recommend this course to anyone who wishes to participate, it worth the effort!
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