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Jay Alammar,
Arpan Chakraborty,
Luis Serrano,
and
Dana Sheahen
Register for this course and see more details by visiting:
OpenCourser.com/course/t8tjo2/tensorflo
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What's inside
Syllabus
In this section you'll get a hands-on introduction to TensorFlow, Google's deep learning framework, and you'll be able to apply it on an image dataset.
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Provides a hands-on introduction to TensorFlow, Google's deep learning framework, and enables students to apply it
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Save TensorFlow to your list so you can find it easily later:
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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 TensorFlow with these
activities:
Follow a TensorFlow tutorial on image classification
Show steps
Following a guided tutorial will provide a structured approach to learning the basics of image classification with TensorFlow.
Browse courses on
Image Recognition
Show steps
-
Find a TensorFlow tutorial on image classification
-
Follow the steps in the tutorial
-
Run the code and observe the results
Practice importing images and labeling data
Show steps
Practice importing images and labeling data, which are fundamental skills for working with image datasets in TensorFlow.
Show steps
-
Find a dataset of images
-
Import the images into TensorFlow
-
Label the images with their corresponding classes
Curate a collection of TensorFlow resources
Show steps
Curating a collection of TensorFlow resources will help you organize and synthesize your learning.
Show steps
-
Gather resources such as tutorials, documentation, and code examples
-
Organize the resources by topic or category
-
Share your collection with others
Three other activities
Expand to see all activities and additional details
Show all six activities
Participate in a TensorFlow competition
Show steps
Participating in a TensorFlow competition will challenge you to apply your skills and knowledge in a real-world setting.
Browse courses on
Kaggle Competition
Show steps
-
Find a TensorFlow competition
-
Register for the competition
-
Submit your solution
Create a blog post or video explaining a TensorFlow concept
Show steps
Creating a blog post or video will reinforce your understanding of TensorFlow concepts and help you communicate your knowledge to others.
Show steps
-
Choose a TensorFlow concept to explain
-
Write or record your explanation
-
Publish or share your blog post or video
Mentor a beginner in TensorFlow
Show steps
Mentoring a beginner will reinforce your understanding of TensorFlow and help you develop your communication and teaching skills.
Show steps
-
Find a beginner who is interested in learning TensorFlow
-
Set up regular meetings or communication channels
-
Provide guidance and support on TensorFlow concepts and projects
Follow a TensorFlow tutorial on image classification
Show steps
Following a guided tutorial will provide a structured approach to learning the basics of image classification with TensorFlow.
Browse courses on
Image Recognition
Show steps
Show steps
Show steps
- Find a TensorFlow tutorial on image classification
- Follow the steps in the tutorial
- Run the code and observe the results
Practice importing images and labeling data
Show steps
Practice importing images and labeling data, which are fundamental skills for working with image datasets in TensorFlow.
Show steps
Show steps
Show steps
- Find a dataset of images
- Import the images into TensorFlow
- Label the images with their corresponding classes
Curate a collection of TensorFlow resources
Show steps
Curating a collection of TensorFlow resources will help you organize and synthesize your learning.
Show steps
Show steps
Show steps
- Gather resources such as tutorials, documentation, and code examples
- Organize the resources by topic or category
- Share your collection with others
Three other activities
Expand to see all activities and additional details
Show all six activities
Participate in a TensorFlow competition
Show steps
Participating in a TensorFlow competition will challenge you to apply your skills and knowledge in a real-world setting.
Browse courses on
Kaggle Competition
Show steps
Show steps
Show steps
- Find a TensorFlow competition
- Register for the competition
- Submit your solution
Create a blog post or video explaining a TensorFlow concept
Show steps
Creating a blog post or video will reinforce your understanding of TensorFlow concepts and help you communicate your knowledge to others.
Show steps
Show steps
Show steps
- Choose a TensorFlow concept to explain
- Write or record your explanation
- Publish or share your blog post or video
Mentor a beginner in TensorFlow
Show steps
Mentoring a beginner will reinforce your understanding of TensorFlow and help you develop your communication and teaching skills.
Show steps
Show steps
Show steps
- Find a beginner who is interested in learning TensorFlow
- Set up regular meetings or communication channels
- Provide guidance and support on TensorFlow concepts and projects
Career center
Learners who complete TensorFlow will develop knowledge and skills
that may be useful to these careers:
Machine Learning Researcher
Machine Learning Researcher
Machine Learning Researchers develop new machine learning algorithms and techniques. TensorFlow is one of the most popular frameworks for machine learning research, making this course especially relevant to someone aiming to pursue a career in this field.
This course will help build a foundation for a career as a Machine Learning Researcher. It will teach the basics of TensorFlow and its use in machine learning research.
Deep Learning Engineer
Deep Learning Engineer
A Deep Learning Engineer is a specialized type of Machine Learning Engineer who focuses on developing and implementing deep learning models. TensorFlow is one of the most popular frameworks for deep learning, making this course especially relevant to someone aiming to pursue a career in this field.
This course will help someone build a foundation for a career as a Deep Learning Engineer. It will teach them the basics of TensorFlow and its use in deep learning.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer combines coding skills with an understanding of machine learning algorithms and statistical modeling to design, build, test, and deploy machine learning systems. This course specifically teaches the use of the TensorFlow framework, which will appeal to an employer seeking to hire a Machine Learning Engineer.
Taking this course will help someone gain or refine the technical skills needed to succeed in this role. It will also introduce them to some of the core concepts of machine learning, such as supervised learning, unsupervised learning, and reinforcement learning.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers design and develop systems that can interpret and understand images and videos. TensorFlow is one of the leading frameworks for computer vision, making this course especially relevant to someone aiming to pursue a career in this field.
This course will help build a foundation for a career as a Computer Vision Engineer. It will teach the basics of TensorFlow and its use in computer vision.
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers design and develop systems that can understand and generate human language. TensorFlow is one of the leading frameworks for natural language processing, making this course especially relevant to someone aiming to pursue a career in this field.
This course will help build a foundation for a career as a Natural Language Processing Engineer. It will teach the basics of TensorFlow and its use in natural language processing.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers design, develop, and maintain artificial intelligence systems. TensorFlow is commonly used in the field of AI, making this course useful to an aspiring AI Engineer.
By taking this course, someone can develop the skills needed to build and deploy AI systems using TensorFlow. This will give them a competitive advantage in the job market.
Data Scientist
Data Scientist
The field of Data Science combines Machine Learning, Artificial Intelligence, and Statistics to make sense of large data sets. It combines the ability to build and deploy models with TensorFlow, as taught in this course, with analytical skills to make predictions and recommendations from data.
This course may help students to develop or refine the skills needed to become a Data Scientist, including the ability to clean, prepare, and analyze data, and to build and deploy models using TensorFlow. A Data Scientist who has taken this course will have an advantage in their ability to manage and interpret large data sets.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. This course can help a Quantitative Analyst to learn how to use TensorFlow to create and deploy machine learning models. This can be used to improve the accuracy of predictions and to identify new opportunities.
A Quantitative Analyst who takes this course will have an advantage in the job market.
Robotics Engineer
Robotics Engineer
Robotics Engineers design, build, and maintain robots. TensorFlow is being used in robotics to develop new applications, such as self-driving cars and drones. By taking this course, someone can develop the skills they need to use TensorFlow to build and deploy machine learning models in robotics.
A Robotics Engineer who takes this course will have an advantage in the job market.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products and features. TensorFlow is an open-source machine learning library used by many companies, such as Google, Uber, and Airbnb, to develop machine learning products and features. This course will help someone develop the skills they need to be successful as a Product Manager.
Taking this course will help a Product Manager to better understand the technical aspects of machine learning and how to apply it to product development. This will give them a competitive advantage in the job market.
Data Analyst
Data Analyst
Data Analysts combine their knowledge of data analysis tools and techniques with their understanding of business problems to extract meaningful insights from data. This course can help a Data Analyst build the skills needed to organize and analyze large data sets using TensorFlow, a powerful open-source machine learning library.
Data Analysts who take this course will be better positioned to understand and apply machine learning techniques to their work. It will help them to automate tasks, identify trends, and make better decisions.
Research Scientist
Research Scientist
Research Scientists conduct research and develop new technologies and products. This course provides a comprehensive introduction to TensorFlow, which is one of the most popular frameworks for deep learning. It will appeal to a Research Scientist interested in applying deep learning to their research.
A Research Scientist who takes this course will have an advantage when using TensorFlow for research purposes.
Data Engineer
Data Engineer
A Data Engineer is responsible for designing and building the infrastructure that stores and processes data. By taking this course, they can develop the skills needed to use TensorFlow to build and deploy machine learning models. This can help to improve the efficiency of data processing and to make better use of data.
A Data Engineer who has taken this course will be better prepared for the challenges of working with big data.
Software Engineer
Software Engineer
Software Engineers apply the principles of computer science and software design to the creation of computer software. Those interested in using machine learning and deep learning within software applications may be interested in taking this course, as it provides a comprehensive introduction to TensorFlow, one of the leading frameworks for these purposes.
A Software Engineer who has taken this course will have an advantage in their ability to integrate TensorFlow into software applications.
Business Analyst
Business Analyst
Business Analysts use their knowledge of business and technology to help organizations improve their performance. By taking this course, they can develop the skills needed to use machine learning to solve business problems. This can help increase efficiency and productivity.
A Business Analyst who has taken this course will have a better understanding of how machine learning can be used to improve business processes.
For more career information including salaries, visit:
OpenCourser.com/course/t8tjo2/tensorflo
Reading list
We've selected 11 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
TensorFlow.
Provides a comprehensive overview of deep learning, covering the fundamental concepts, architectures, and applications. It is particularly useful for beginners who want to build a strong foundation in deep learning.
Offers a practical guide to machine learning, using popular Python libraries such as Scikit-Learn, Keras, and TensorFlow. It valuable resource for anyone who wants to gain hands-on experience in machine learning.
Save
Comprehensive reference on deep learning, covering the mathematical foundations, architectures, and applications of deep learning. It valuable resource for researchers and practitioners in the field.
Save
Provides a comprehensive overview of machine learning, covering topics such as supervised learning, unsupervised learning, and reinforcement learning. It valuable resource for students and practitioners who want to gain a deep understanding of machine learning.
Provides a comprehensive overview of pattern recognition and machine learning, covering topics such as Bayesian inference, support vector machines, and neural networks. It valuable resource for researchers and practitioners in the field.
Save
Provides a comprehensive overview of deep learning using the R programming language. It valuable resource for data scientists and analysts who want to use R for deep learning.
Provides a comprehensive overview of machine learning using the Python programming language. It valuable resource for data scientists and analysts who want to use Python for machine learning.
Provides a comprehensive overview of statistical learning, covering topics such as linear regression, logistic regression, and decision trees. It valuable resource for data scientists and analysts who want to gain a deep understanding of statistical learning.
Save
Provides a comprehensive overview of data mining, covering topics such as data preprocessing, feature selection, and model evaluation. It valuable resource for data scientists and analysts who want to gain a deep understanding of data mining.
Provides a broad overview of artificial intelligence, covering topics such as the history of AI, the different types of AI, and the ethical implications of AI. It great choice for anyone who wants to learn more about AI.
Provides a practical guide to machine learning using the Python programming language. It valuable resource for data scientists and analysts who want to use Python for machine learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/t8tjo2/tensorflo
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Time
120 hours
Level
Advanced
Via
Udacity
Instructors
Jay Alammar
Arpan Chakraborty
Luis Serrano
Dana Sheahen
Language
English
Good to know
Provides a hands-on introduction to TensorFlow, Google's deep learning framework, and enables students to apply it
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