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Vincent Vanhoucke
and
Arpan Chakraborty
Machine learning is one of the fastest-growing and most exciting fields out there, and deep learning represents its true bleeding edge. In this course, you’ll develop a clear understanding of the motivation for deep learning, and design intelligent systems that learn from complex and/or large-scale datasets.
Read more
Machine learning is one of the fastest-growing and most exciting fields out there, and deep learning represents its true bleeding edge. In this course, you’ll develop a clear understanding of the motivation for deep learning, and design intelligent systems that learn from complex and/or large-scale datasets.
Read more
Machine learning is one of the fastest-growing and most exciting fields out there, and deep learning represents its true bleeding edge. In this course, you’ll develop a clear understanding of the motivation for deep learning, and design intelligent systems that learn from complex and/or large-scale datasets.
We’ll show you how to train and optimize basic neural networks, convolutional neural networks, and long short term memory networks. Complete learning systems in TensorFlow will be introduced via projects and assignments. You will learn to solve new classes of problems that were once thought prohibitively challenging, and come to better appreciate the complex nature of human intelligence as you solve these same problems effortlessly using deep learning methods.
We have developed this course with Vincent Vanhoucke, Principal Scientist at Google, and technical lead in the Google Brain team.
**Note: This is an intermediate to advanced level course offered as part of the Machine Learning Engineer Nanodegree program. It assumes you have taken a first course in machine learning, and that you are at least familiar with supervised learning methods.
Register for this course and see more details by visiting:
OpenCourser.com/course/3rxhv4/udacity
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possible dealbreakers
Digs into deep learning, a rapidly evolving and crucial field
Teaches students to design and build AI systems that learn from large and complex data
Provides hands-on experience through projects and assignments to tackle real-world challenges
Leverages TensorFlow, an industry-standard framework, for practical implementation
Taught by Vincent Vanhoucke, a renowned expert in deep learning with Google Brain
Presumes a foundational understanding of machine learning and supervised learning, requiring prior coursework
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Deep Learning with these
activities:
Connect with experts and researchers in deep learning
Show steps
Provides students with access to experienced professionals, offering guidance and insights beyond the classroom.
Browse courses on
Deep Learning
Show steps
-
Identify potential mentors.
-
Reach out and introduce yourself.
-
Schedule meetings or virtual sessions.
Review basic calculus
Show steps
Start off by getting a clear idea of your footing in Calculus
Show steps
-
Review your notes from your previous courses
-
Go through chapters related to general Calculus I topics like limits and differentiation in your textbook
-
Solve some problems from your old homework assignments or the textbook
Review 'Deep Learning' by Yoshua Bengio
Show steps
Introduces fundamental concepts of deep learning and provides a solid theoretical foundation for the course.
View
Deep Learning
on Amazon
Show steps
-
Read the preface and introduction.
-
Review the chapters on supervised learning and neural networks.
-
Complete the exercises and review the solutions.
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Review basic linear algebra
Show steps
Get comfortable with matrix and vector operations again
Browse courses on
Linear Algebra
Show steps
-
Go over your lecture notes and materials from your previous course
-
Download some past homeworks or practice problems from your university website
-
Finish the problems on your own or consult the provided solutions
Participate in a study group with other students
Show steps
Fosters collaboration, discussion, and peer learning, enhancing the understanding of course material.
Browse courses on
Deep Learning
Show steps
-
Find a group of fellow students.
-
Set regular meeting times.
-
Review course material together.
-
Discuss concepts and ask questions.
Implement a basic neural network in TensorFlow
Show steps
Provides hands-on experience with implementing and training a neural network, reinforcing the concepts learned in the course.
Browse courses on
Neural Networks
Show steps
-
Set up a TensorFlow development environment.
-
Create a simple neural network architecture.
-
Train the network on a small dataset.
-
Evaluate the performance of the trained network.
Attend a workshop on deep learning applications
Show steps
Exposes students to practical applications of deep learning in various domains, broadening their understanding of its real-world impact.
Browse courses on
Deep Learning
Show steps
-
Research and find relevant workshops.
-
Register and attend the workshop.
-
Actively participate in sessions and discussions.
Create a blog post explaining a deep learning concept
Show steps
Encourages students to synthesize their understanding of deep learning concepts and communicate them effectively.
Browse courses on
Deep Learning
Show steps
-
Choose a specific deep learning concept.
-
Research and gather information about the concept.
-
Organize your thoughts and create an outline.
-
Write the blog post, ensuring clarity and accuracy.
-
Publish the blog post and share it with others.
Follow tutorials on advanced deep learning techniques
Show steps
Provides exposure to cutting-edge deep learning techniques and expands students' knowledge beyond the scope of the course.
Browse courses on
Deep Learning
Show steps
-
Identify relevant tutorials on advanced techniques.
-
Follow the tutorials step-by-step.
-
Implement the techniques in your own projects.
Develop a deep learning solution for a real-world problem
Show steps
Applies deep learning concepts to solve real-world problems, demonstrating practical application and enhancing problem-solving skills.
Browse courses on
Deep Learning
Show steps
-
Identify a suitable problem.
-
Gather and preprocess data.
-
Design and implement a deep learning model.
-
Evaluate and refine the model.
-
Present the solution in a detailed report.
Connect with experts and researchers in deep learning
Show steps
Provides students with access to experienced professionals, offering guidance and insights beyond the classroom.
Browse courses on
Deep Learning
Show steps
Show steps
Show steps
- Identify potential mentors.
- Reach out and introduce yourself.
- Schedule meetings or virtual sessions.
Review basic calculus
Show steps
Start off by getting a clear idea of your footing in Calculus
Show steps
Show steps
Show steps
- Review your notes from your previous courses
- Go through chapters related to general Calculus I topics like limits and differentiation in your textbook
- Solve some problems from your old homework assignments or the textbook
Review 'Deep Learning' by Yoshua Bengio
Show steps
Introduces fundamental concepts of deep learning and provides a solid theoretical foundation for the course.
View
Deep Learning
on Amazon
Show steps
Show steps
Show steps
- Read the preface and introduction.
- Review the chapters on supervised learning and neural networks.
- Complete the exercises and review the solutions.
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Review basic linear algebra
Show steps
Get comfortable with matrix and vector operations again
Browse courses on
Linear Algebra
Show steps
Show steps
Show steps
- Go over your lecture notes and materials from your previous course
- Download some past homeworks or practice problems from your university website
- Finish the problems on your own or consult the provided solutions
Participate in a study group with other students
Show steps
Fosters collaboration, discussion, and peer learning, enhancing the understanding of course material.
Browse courses on
Deep Learning
Show steps
Show steps
Show steps
- Find a group of fellow students.
- Set regular meeting times.
- Review course material together.
- Discuss concepts and ask questions.
Implement a basic neural network in TensorFlow
Show steps
Provides hands-on experience with implementing and training a neural network, reinforcing the concepts learned in the course.
Browse courses on
Neural Networks
Show steps
Show steps
Show steps
- Set up a TensorFlow development environment.
- Create a simple neural network architecture.
- Train the network on a small dataset.
- Evaluate the performance of the trained network.
Attend a workshop on deep learning applications
Show steps
Exposes students to practical applications of deep learning in various domains, broadening their understanding of its real-world impact.
Browse courses on
Deep Learning
Show steps
Show steps
Show steps
- Research and find relevant workshops.
- Register and attend the workshop.
- Actively participate in sessions and discussions.
Create a blog post explaining a deep learning concept
Show steps
Encourages students to synthesize their understanding of deep learning concepts and communicate them effectively.
Browse courses on
Deep Learning
Show steps
Show steps
Show steps
- Choose a specific deep learning concept.
- Research and gather information about the concept.
- Organize your thoughts and create an outline.
- Write the blog post, ensuring clarity and accuracy.
- Publish the blog post and share it with others.
Follow tutorials on advanced deep learning techniques
Show steps
Provides exposure to cutting-edge deep learning techniques and expands students' knowledge beyond the scope of the course.
Browse courses on
Deep Learning
Show steps
Show steps
Show steps
- Identify relevant tutorials on advanced techniques.
- Follow the tutorials step-by-step.
- Implement the techniques in your own projects.
Develop a deep learning solution for a real-world problem
Show steps
Applies deep learning concepts to solve real-world problems, demonstrating practical application and enhancing problem-solving skills.
Browse courses on
Deep Learning
Show steps
Show steps
Show steps
- Identify a suitable problem.
- Gather and preprocess data.
- Design and implement a deep learning model.
- Evaluate and refine the model.
- Present the solution in a detailed report.
Career center
Learners who complete Deep Learning will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist plays an increasingly important role in the business decision-making process. Through Deep Learning's design of intelligent systems that learn from complex datasets, a Data Scientist is able to gain insights into data that may not be discernible otherwise. This course's focus on advanced machine learning concepts such as neural networks, convolutional neural networks, and long short term memory networks will help a Data Scientist become more skilled at solving complex problems that plague many organizations today.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers work to build, deploy, and monitor machine learning models. This often involves using their understanding of Deep Learning to design and implement machine learning systems that can solve real-world problems. The course's focus on training and optimizing neural networks and the introduction of complete learning systems in Tensorflow will be invaluable to a Machine Learning Engineer who is looking to advance their knowledge of the field.
Deep Learning Researcher
Deep Learning Researcher
A Deep Learning Researcher conducts research in the field of deep learning, which is a subfield of machine learning. Deep Learning Researchers work to develop and improve deep learning algorithms and models, as well as explore new applications for deep learning. The course's focus on advanced concepts in Deep Learning, such as neural networks, convolutional neural networks, and long short term memory networks, would be of great interest to a Deep Learning Researcher.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers research, design, develop, and test AI algorithms and systems. The course's focus on advanced concepts in Deep Learning, such as neural networks, convolutional neural networks, and long short term memory networks, would aid an Artificial Intelligence Engineer in learning more about how to build and improve AI systems.
Software Engineer
Software Engineer
Software Engineers design, develop, test, deploy, and maintain software systems. Deep Learning is increasingly used to build and improve software systems, and the course's focus on training and optimizing neural networks and the introduction of complete learning systems in Tensorflow would help a Software Engineer stay abreast of the latest developments in this field.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to help organizations make better decisions. The course's focus on designing intelligent systems that learn from complex datasets would be of great value to a Data Analyst who is looking to improve their skills in this field.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data systems. Deep Learning is increasingly used to build and improve data systems, and the course's focus on training and optimizing neural networks and the introduction of complete learning systems in Tensorflow would be of great value to a Data Engineer who is looking to improve their skills in this field.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical methods to analyze data and make predictions. The course's focus on designing intelligent systems that learn from complex datasets would be of great value to a Quantitative Analyst who is looking to improve their skills in this field.
Product Manager
Product Manager
Product Managers are responsible for the planning, development, and marketing of products. Deep Learning is increasingly used to build and improve products, and the course's focus on training and optimizing neural networks and the introduction of complete learning systems in Tensorflow would be of great value to a Product Manager who is looking to improve their skills in this field.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to solve complex problems for organizations. The course's focus on designing intelligent systems that learn from complex datasets would be of great value to an Operations Research Analyst who is looking to improve their skills in this field.
Business Analyst
Business Analyst
Business Analysts help organizations to improve their performance by analyzing data and identifying opportunities for improvement. The course's focus on designing intelligent systems that learn from complex datasets would be of great value to a Business Analyst who is looking to improve their skills in this field.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. The course's focus on designing intelligent systems that learn from complex datasets would be of great value to a Statistician who is looking to improve their skills in this field.
Financial Analyst
Financial Analyst
Financial Analysts use financial data to make recommendations to investors and businesses. The course's focus on designing intelligent systems that learn from complex datasets would be of great value to a Financial Analyst who is looking to improve their skills in this field.
Market Researcher
Market Researcher
Market Researchers conduct research to understand consumer behavior and market trends. The course's focus on designing intelligent systems that learn from complex datasets would be of great value to a Market Researcher who is looking to improve their skills in this field.
Management Consultant
Management Consultant
Management Consultants advise organizations on how to improve their performance. The course's focus on designing intelligent systems that learn from complex datasets would be of great value to a Management Consultant who is looking to improve their skills in this field.
For more career information including salaries, visit:
OpenCourser.com/course/3rxhv4/udacity
Reading list
We've selected six books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Deep Learning.
Save
Comprehensive textbook on deep learning, covering the basics of neural networks, convolutional neural networks, recurrent neural networks, and more. It valuable resource for anyone who wants to learn more about deep learning.
Practical guide to machine learning using Scikit-Learn, Keras, and TensorFlow. It covers the basics of machine learning, as well as more advanced topics such as deep learning and natural language processing.
Practical guide to machine learning using R. It covers the basics of machine learning, as well as more advanced topics such as deep learning and natural language processing.
Practical guide to deep learning using Python. It covers the basics of deep learning, as well as more advanced topics such as convolutional neural networks and recurrent neural networks.
Comprehensive introduction to neural networks and deep learning. It valuable resource for anyone who wants to learn more about the theoretical foundations of deep learning.
Comprehensive guide to deep learning for natural language processing. It covers the basics of natural language processing, as well as more advanced topics such as deep learning models for text classification, text generation, and machine translation.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/3rxhv4/udacity
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Via
Udacity
Instructors
Vincent Vanhoucke
Arpan Chakraborty
Good to know
Digs into deep learning, a rapidly evolving and crucial field
Teaches students to design and build AI systems that learn from large and complex data
Provides hands-on experience through projects and assignments to tackle real-world challenges
Leverages TensorFlow, an industry-standard framework, for practical implementation
Taught by Vincent Vanhoucke, a renowned expert in deep learning with Google Brain
Presumes a foundational understanding of machine learning and supervised learning, requiring prior coursework
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