Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning from Coursera

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.

The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.

What's inside

Syllabus

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. To get started, check out the first video, a conversation between Andrew and Laurence that sets the theme for what you'll study...

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! Check out this conversation between Laurence and Andrew where they discuss it and introduce you to Computer Vision!

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.

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!

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Introduces basic and advanced concepts of Tensorflow for scalable AI-powered algorithms

Taught by Laurence Moroney, who is widely recognized for his work in TensorFlow and AI

Emphasizes a new programming paradigm for solving computer vision problems

Involves building and applying scalable models to real-world problems

May not cover all the foundational principles of Machine Learning and Deep Learning

Reviews summary

Introduction to tensorflow

learners say this is a great introduction to Tensorflow, especially for beginners. Students who have taken Andrew Ng's Deep Learning Specialization may find it too easy. The course starts with implementing a simple neural network and then progresses onto convolutional neural networks. It ends with a very useful data management topic on training data labelling. One of the major benefits of this course is that you can start learning by doing right from week 1. The instructor doesn't spend time explaining every line of code with every detail. That leaves you to figure out a few things on your own due to which you're bound to remember these details.

The instructor has a clear and to the point, with some good exercises.

"The instructor has a clear and to the point, with some good exercises."

This course is coming for me after the Machine Learning course from Andrew Ng and it gives very hands-on answer to theorical part deep dived. Tensorflow is really easy to jump in, and this course give a perfect overview of the potentiel.

"This course is coming for me after the Machine Learning course from Andrew Ng and it gives very hands-on answer to theorical part deep dived."

"Tensorflow is really easy to jump in, and this course give a perfect overview of the potentiel."

The course is well paced, the assignments balanced, and overall provided a lot of experience in learning real-world usage of neural networks.

"The course is well paced, the assignments balanced, and overall provided a lot of experience in learning real-world usage of neural networks."

The course is heavily focused on hands-on application using Python. The course will encourage you to experiment and understand the impact of different parameters in your model. It's fun and challenging.

"The course will encourage you to experiment and understand the impact of different parameters in your model."

"It's fun and challenging."

Each week you will have like 2 minute video explaining the NN that you will use.

"Each week you will have like 2 minute video explaining the NN that you will use."

This course is really about Keras and not tensorflow.

"This course is really about Keras and not tensorflow."

In comparison to the deep learning specialization assignments, the ones we had in these course are really poor in terms of information and clarity on what we have to do.

"In comparison to the deep learning specialization assignments, the ones we had in these course are really poor in terms of information and clarity on what we have to do."

Career center

Learners who complete Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data scientists use TensorFlow to analyze data and build machine learning models. This course will teach you how to use TensorFlow to perform data analysis and build machine learning models, which can help you to become a successful data scientist.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine learning engineers use TensorFlow to build and implement machine learning models. This course will teach you how to use TensorFlow to develop and deploy machine learning models, which can help you to advance your career as a machine learning engineer.

See salaries and explore the career path for Machine Learning Engineer

Software Engineer

TensorFlow is a popular open-source framework for machine learning, and it is used by many software engineers to build scalable AI-powered algorithms. This course will teach you best practices for using TensorFlow, which can help you to develop the skills needed to become a successful software engineer in the field of artificial intelligence and machine learning.

See salaries and explore the career path for Software Engineer

Speech Recognition Engineer

Speech recognition engineers use TensorFlow to build and implement speech recognition systems. This course will teach you how to use TensorFlow to develop and deploy speech recognition systems, which can help you to advance your career as a speech recognition engineer.

See salaries and explore the career path for Speech Recognition Engineer

Computer Vision Engineer

Computer vision engineers use TensorFlow to build and implement computer vision systems. This course will teach you how to use TensorFlow to develop and deploy computer vision systems, which can help you to advance your career as a computer vision engineer.

See salaries and explore the career path for Computer Vision Engineer

Artificial Intelligence Engineer

Artificial intelligence engineers use TensorFlow to build and implement artificial intelligence systems. This course will teach you how to use TensorFlow to develop and deploy artificial intelligence systems, which can help you to advance your career as an artificial intelligence engineer.

See salaries and explore the career path for Artificial Intelligence Engineer

Natural Language Processing Engineer

Natural language processing engineers use TensorFlow to build and implement natural language processing systems. This course will teach you how to use TensorFlow to develop and deploy natural language processing systems, which can help you to advance your career as a natural language processing engineer.

See salaries and explore the career path for Natural Language Processing Engineer

Deep Learning Engineer

Deep learning engineers use TensorFlow to build and implement deep learning models. This course will teach you how to use TensorFlow to develop and deploy deep learning models, which can help you to advance your career as a deep learning engineer.

See salaries and explore the career path for Deep Learning Engineer

Machine Learning Researcher

Machine learning researchers use TensorFlow to develop new machine learning algorithms and techniques. This course will teach you how to use TensorFlow to conduct machine learning research, which can help you to advance your career as a machine learning researcher.

See salaries and explore the career path for Machine Learning Researcher

Deep Learning Researcher

Deep learning researchers use TensorFlow to develop new deep learning algorithms and techniques. This course will teach you how to use TensorFlow to conduct deep learning research, which can help you to advance your career as a deep learning researcher.

See salaries and explore the career path for Deep Learning Researcher

Computer Vision Researcher

Computer vision researchers use TensorFlow to develop new computer vision algorithms and techniques. This course will teach you how to use TensorFlow to conduct computer vision research, which can help you to advance your career as a computer vision researcher.

See salaries and explore the career path for Computer Vision Researcher

Natural Language Processing Researcher

Natural language processing researchers use TensorFlow to develop new natural language processing algorithms and techniques. This course will teach you how to use TensorFlow to conduct natural language processing research, which can help you to advance your career as a natural language processing researcher.

See salaries and explore the career path for Natural Language Processing Researcher

Speech Recognition Researcher

Speech recognition researchers use TensorFlow to develop new speech recognition algorithms and techniques. This course will teach you how to use TensorFlow to conduct speech recognition research, which can help you to advance your career as a speech recognition researcher.

See salaries and explore the career path for Speech Recognition Researcher

Artificial Intelligence Professor

Artificial intelligence professors use TensorFlow to teach artificial intelligence and machine learning courses. This course will teach you how to use TensorFlow to develop and deliver artificial intelligence and machine learning courses, which can help you to advance your career as an artificial intelligence professor.

See salaries and explore the career path for Artificial Intelligence Professor

Machine Learning Professor

Machine learning professors use TensorFlow to teach machine learning courses. This course will teach you how to use TensorFlow to develop and deliver machine learning courses, which can help you to advance your career as a machine learning professor.

See salaries and explore the career path for Machine Learning Professor

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

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