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Image Colorization using TensorFlow 2 and Keras

Vinita Silaparasetty
This guided project is about image colorization using TensorFlow2 and Keras. Image colorization comes under the computer vision domain. In this project you will learn how to build a convolutional neural network(CNN) using Tensorflow2 and Keras. While you are watching me code, you will get a cloud desktop with all the required software pre-installed. This will allow you to code along with me. After all, we learn best with active, hands-on learning. Special Feature: 1) Explanation of the process of image colorization. 2) How to reshape data to fit a CNN. 3) Explanation of each layer in a CNN. 4) Create a Streamlit app to allow...
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This guided project is about image colorization using TensorFlow2 and Keras. Image colorization comes under the computer vision domain. In this project you will learn how to build a convolutional neural network(CNN) using Tensorflow2 and Keras. While you are watching me code, you will get a cloud desktop with all the required software pre-installed. This will allow you to code along with me. After all, we learn best with active, hands-on learning. Special Feature: 1) Explanation of the process of image colorization. 2) How to reshape data to fit a CNN. 3) Explanation of each layer in a CNN. 4) Create a Streamlit app to allow users to colorize a black and white image using the model you trained. Note: This project works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Suitable for learners interested in computer vision applications
Involves working on a practical project, fostering hands-on learning
Taught by instructors with expertise in the field

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Reviews summary

Disappointingly sparse tensorflow

With 3 reviews sampled, learners think the TensorFlow course is not a good investment of time. Reviewers complain that the instructor is a poor communicator, the code is broken, and that the high-level TensorFlow concepts are not explained. Because of the high number of negative reviews for this course, it is recommended that you begin your learning journey elsewhere.

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 Image Colorization using TensorFlow 2 and Keras with these activities:
Organize Course Materials
Organize notes, assignments, and other course materials to facilitate review and enhance understanding.
Show steps
  • Create a structured folder system
  • Categorize and label materials
Review Python
Refresh Python skills to ensure proficiency in implementing the course concepts.
Browse courses on Python
Show steps
  • Review Python syntax
  • Practice Python exercises
Python Programming Review
Refreshing your Python programming skills will help you to be more successful in this course.
Browse courses on Python Programming
Show steps
  • Review the basics of Python programming.
  • Complete some Python programming exercises.
20 other activities
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Read 'Deep Learning with TensorFlow 2 and Keras' by Antonio Gulli and Amita Kapoor
Build a solid foundation in TensorFlow and Keras before beginning the course.
View Deep Learning with TensorFlow and Keras - Third... on Amazon
Show steps
  • Read Chapter 1: Introduction to TensorFlow and Keras
  • Read Chapter 2: Building and Training Neural Networks
Mentor a junior student who is taking this course
Reinforce your own understanding while supporting a junior student's learning journey.
Show steps
  • Identify a junior student who needs support
  • Provide guidance and support on course material and assignments
Review Prerequisites
Review the basics of image processing and computer vision to ensure a solid foundation for the course.
Browse courses on Image Processing
Show steps
  • Review image manipulation techniques
  • Review computer vision algorithms
Deep Learning with Python
Reading this book will help you to learn the fundamentals of deep learning.
View Deep Learning with Python, Second Edition on Amazon
Show steps
  • Read the book.
  • Complete the exercises in the book.
Complete the TensorFlow and Keras tutorial series by Google
Reinforce your understanding of TensorFlow and Keras by following a structured tutorial series.
Browse courses on TensorFlow
Show steps
  • Complete the 'Getting Started with TensorFlow' tutorial
  • Complete the 'Building a Neural Network with Keras' tutorial
Image Colorization Resource List
Creating a resource list will help you to organize your knowledge of image colorization.
Show steps
  • Create a list of resources on image colorization.
  • Categorize the resources.
  • Share the resource list with others.
TensorFlow Tutorials
Explore TensorFlow tutorials to supplement the course material and gain additional practical skills.
Show steps
  • Follow a TensorFlow tutorial
  • Implement the tutorial in your own code
Image Colorization Tutorial
Following tutorials will help you to learn the basics of image colorization.
Show steps
  • Find a tutorial on image colorization.
  • Follow the steps in the tutorial.
  • Experiment with different parameters.
Attend a Computer Vision Workshop
Attending a workshop will help you to learn about the latest advances in computer vision.
Browse courses on Computer Vision
Show steps
  • Find a computer vision workshop.
  • Register for the workshop.
  • Attend the workshop.
Study Group
Participating in a study group will help you to learn from your peers and to improve your understanding of the material.
Show steps
  • Find a study group.
  • Attend the study group meetings.
  • Participate in the discussions.
Practice building simple CNNs using TensorFlow and Keras
Develop proficiency in building and training CNNs, which are essential for image colorization.
Browse courses on TensorFlow
Show steps
  • Build a simple CNN for image classification
  • Train the CNN on a small dataset of colorized images
CNN Exercises
Practice implementing and training CNNs to improve understanding of their architecture and functionality.
Browse courses on Convolutional Neural Networks
Show steps
  • Build a simple CNN model
  • Train the model on a dataset
  • Evaluate the model's performance
Join a study group for this course
Engage with other students to discuss course material, share insights, and deepen your understanding.
Show steps
  • Find a study group or create your own
  • Meet regularly to discuss course material and assignments
Tensorflow Practice Problems
Practice problems will help to reinforce your understanding of the concepts covered in the course.
Browse courses on TensorFlow
Show steps
  • Visit the official TensorFlow website and complete the practice exercises.
  • Find additional practice problems online.
Mentor a Beginner
Mentoring others will help you to solidify your understanding of the concepts covered in the course.
Browse courses on Mentoring
Show steps
  • Find a beginner who is interested in learning about image colorization.
  • Share your knowledge and experience with the beginner.
  • Answer the beginner's questions.
Write a blog post or article about image colorization using TensorFlow and Keras
Share your knowledge and insights about image colorization by creating a blog post or article.
Browse courses on TensorFlow
Show steps
  • Choose a topic related to image colorization
  • Research and write the blog post or article
Colorize an Image Project
By completing a project, you will be able to apply the concepts you have learned in the course to a real-world problem.
Show steps
  • Choose an image to colorize.
  • Use the techniques you have learned in the course to colorize the image.
  • Share your results with others.
Image Colorization Project
Develop a CNN-based image colorization tool to demonstrate practical application and deep understanding of the course concepts.
Show steps
  • Train the model
  • Design the CNN architecture
  • Create a user interface
Create a web app for image colorization using Streamlit
Apply your skills to build a web app that demonstrates your understanding of image colorization and web development.
Browse courses on TensorFlow
Show steps
  • Develop the backend of the web app using TensorFlow and Keras for image colorization
  • Create the frontend of the web app using Streamlit
Participate in a Kaggle competition related to image colorization
Challenge yourself and showcase your skills by participating in a real-world image colorization competition.
Browse courses on Kaggle
Show steps
  • Identify a suitable Kaggle competition related to image colorization
  • Build a solution using TensorFlow and Keras
  • Submit your solution to the competition

Career center

Learners who complete Image Colorization using TensorFlow 2 and Keras will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
A Machine Learning Engineer develops and implements machine learning models to solve business problems. This course provides a strong foundation in the fundamentals of machine learning, including data preprocessing, model training, and evaluation. It also covers advanced topics such as deep learning and natural language processing. By completing this course, you will gain the skills and knowledge necessary to succeed as a Machine Learning Engineer.
See salaries and explore the career path for Machine Learning Engineer
Data Scientist
A Data Scientist uses data to solve business problems. This course provides a strong foundation in the fundamentals of data science, including data analysis, data visualization, and machine learning. It also covers advanced topics such as big data and cloud computing. By completing this course, you will gain the skills and knowledge necessary to succeed as a Data Scientist.
See salaries and explore the career path for Data Scientist
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course provides a strong foundation in the fundamentals of software engineering, including object-oriented programming, data structures, and algorithms. It also covers advanced topics such as cloud computing and mobile development. By completing this course, you will gain the skills and knowledge necessary to succeed as a Software Engineer.
See salaries and explore the career path for Software Engineer
Computer Vision Engineer
A Computer Vision Engineer develops and implements computer vision algorithms to solve real-world problems. This course provides a strong foundation in the fundamentals of computer vision, including image processing, feature extraction, and object recognition. It also covers advanced topics such as deep learning and augmented reality. By completing this course, you will gain the skills and knowledge necessary to succeed as a Computer Vision Engineer.
See salaries and explore the career path for Computer Vision Engineer
Deep Learning Engineer
A Deep Learning Engineer develops and implements deep learning models to solve business problems. This course provides a strong foundation in the fundamentals of deep learning, including convolutional neural networks, recurrent neural networks, and generative adversarial networks. It also covers advanced topics such as transfer learning and reinforcement learning. By completing this course, you will gain the skills and knowledge necessary to succeed as a Deep Learning Engineer.
See salaries and explore the career path for Deep Learning Engineer
Artificial Intelligence Engineer
An Artificial Intelligence Engineer develops and implements artificial intelligence systems to solve complex problems. This course provides a strong foundation in the fundamentals of artificial intelligence, including machine learning, natural language processing, and computer vision. It also covers advanced topics such as deep learning and reinforcement learning. By completing this course, you will gain the skills and knowledge necessary to succeed as an Artificial Intelligence Engineer.
See salaries and explore the career path for Artificial Intelligence Engineer
Data Analyst
A Data Analyst collects, analyzes, and interprets data to solve business problems. This course provides a strong foundation in the fundamentals of data analysis, including data mining, statistical modeling, and data visualization. It also covers advanced topics such as big data and cloud computing. By completing this course, you will gain the skills and knowledge necessary to succeed as a Data Analyst.
See salaries and explore the career path for Data Analyst
UX Designer
A UX Designer designs and evaluates user interfaces to ensure that they are user-friendly and efficient. This course provides a strong foundation in the fundamentals of UX design, including user research, prototyping, and usability testing. It also covers advanced topics such as mobile design and accessibility. By completing this course, you will gain the skills and knowledge necessary to succeed as a UX Designer.
See salaries and explore the career path for UX Designer
Product Manager
A Product Manager plans and manages the development of new products and features. This course provides a strong foundation in the fundamentals of product management, including market research, product design, and project management. It also covers advanced topics such as agile development and lean product development. By completing this course, you will gain the skills and knowledge necessary to succeed as a Product Manager.
See salaries and explore the career path for Product Manager
Mobile Developer
A Mobile Developer designs, develops, and maintains mobile applications. This course provides a strong foundation in the fundamentals of mobile development, including iOS and Android development. It also covers advanced topics such as cross-platform development and augmented reality. By completing this course, you will gain the skills and knowledge necessary to succeed as a Mobile Developer.
See salaries and explore the career path for Mobile Developer
Game Developer
A Game Developer designs, develops, and maintains video games. This course provides a strong foundation in the fundamentals of game development, including game design, programming, and art. It also covers advanced topics such as artificial intelligence and multiplayer gaming. By completing this course, you will gain the skills and knowledge necessary to succeed as a Game Developer.
See salaries and explore the career path for Game Developer
Web Developer
A Web Developer designs, develops, and maintains websites. This course provides a strong foundation in the fundamentals of web development, including HTML, CSS, and JavaScript. It also covers advanced topics such as responsive design and content management systems. By completing this course, you will gain the skills and knowledge necessary to succeed as a Web Developer.
See salaries and explore the career path for Web Developer
Graphic designer
A Graphic Designer creates visual concepts, using computer software or by hand, to communicate ideas that inspire, inform, and captivate consumers. This course provides a strong foundation in the fundamentals of graphic design, including color theory, typography, and layout. It also covers advanced topics such as branding and user experience design. By completing this course, you will gain the skills and knowledge necessary to succeed as a Graphic Designer.
See salaries and explore the career path for Graphic designer
User Researcher
A User Researcher studies how people use products and services in order to improve their design and usability. This course provides a strong foundation in the fundamentals of user research, including user interviewing, usability testing, and data analysis. It also covers advanced topics such as qualitative research and quantitative research. By completing this course, you will gain the skills and knowledge necessary to succeed as a User Researcher.
See salaries and explore the career path for User Researcher
Technical Writer
A Technical Writer creates and maintains technical documentation, such as user manuals, white papers, and training materials. This course provides a strong foundation in the fundamentals of technical writing, including grammar, style, and organization. It also covers advanced topics such as documentation planning and audience analysis. By completing this course, you will gain the skills and knowledge necessary to succeed as a Technical Writer.
See salaries and explore the career path for Technical Writer

Reading list

We've selected eight 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 Image Colorization using TensorFlow 2 and Keras.
Cover image
Deep Learning with Python, Second Edition
Save
Provides a comprehensive overview of deep learning, from the basics to advanced topics. It valuable resource for anyone who wants to learn more about deep learning and its applications.
Deep Learning with Python, Second Edition
Paperback
$$
Deep Learning with Python, Second Edition
Kindle Edition
$$
Cover image
Deep Learning
Save
Provides a comprehensive overview of convolutional neural networks. It valuable resource for anyone who wants to learn more about convolutional neural networks and their applications.
Deep Learning
Paperback
$$$
Deep Learning (Adaptive Computation and Machine...
Hardcover
$$$
Deep Learning (Adaptive Computation and Machine...
Kindle Edition
$$$
Cover image
Computer Vision
Save
Computer Vision: Algorithms and Applications, by Richard Szeliski, provides a comprehensive overview of the field of computer vision. It covers a wide range of topics, from image formation to object recognition and tracking. The book is well-written and well-organized, and it valuable resource for anyone who wants to learn more about computer vision.
Computer Vision
Paperback
Check
Computer Vision
Kindle Edition
Check
Cover image
Concurrent NumPy in Python
Save
Deep Learning for Computer Vision, by Jason Brownlee, provides a practical guide to using deep learning for computer vision tasks. The book covers a wide range of topics, from image classification to object detection and segmentation. The book is well-written and well-organized, and it valuable resource for anyone who wants to learn more about deep learning for computer vision.
Concurrent NumPy in Python: Faster NumPy With BLAS,...
Paperback
$$
Concurrent NumPy in Python: Faster NumPy With BLAS,...
Kindle Edition
$$
Cover image
Learning OpenCV
Save
Image Processing and Analysis with OpenCV, by Gary Bradski and Adrian Kaehler, provides a comprehensive overview of image processing and analysis with OpenCV. The book covers a wide range of topics, from image acquisition to image segmentation and object recognition. The book is well-written and well-organized, and it valuable resource for anyone who wants to learn more about image processing and analysis with OpenCV.
Learning OpenCV
Paperback
Check
Learning OpenCV
Kindle Edition
Check
Cover image
The Elements of Statistical Learning
Save
The Elements of Statistical Learning, by Trevor Hastie, Robert Tibshirani, and Jerome Friedman, provides a comprehensive overview of statistical learning. The book covers a wide range of topics, from supervised learning to unsupervised learning and reinforcement learning. The book is well-written and well-organized, and it valuable resource for anyone who wants to learn more about statistical learning.
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Kindle Edition
$$$
Machine Learning
Save
Machine Learning, by Tom Mitchell, provides a comprehensive overview of machine learning. The book covers a wide range of topics, from machine learning history to machine learning models and machine learning applications. The book is well-written and well-organized, and it valuable resource for anyone who wants to learn more about machine learning.
Machine Learning (McGraw-Hill International...
Paperback
$$$
Data Mining
Save
Data Mining: Concepts and Techniques, by Jiawei Han, Micheline Kamber, and Jian Pei, provides a comprehensive overview of data mining. The book covers a wide range of topics, from data mining history to data mining models and data mining applications. The book is well-written and well-organized, and it valuable resource for anyone who wants to learn more about data mining.
Data Mining: Concepts and Techniques (The Morgan...
Kindle Edition
$$$
Data Mining: Concepts and Techniques (The Morgan...
Hardcover
$$$
Data Mining: Concepts and Techniques, Second...
Hardcover
$$
Data Mining: Know It All
Hardcover
$$$

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Good to know
Suitable for learners interested in computer vision applications
Involves working on a practical project, fostering hands-on learning
Taught by instructors with expertise in the field
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