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Soumava Dey
The goal of this project is to introduce beginners to the basic concepts of machine learning using TensorFlow. The project will include, how to set up the tool and get started as well as understanding the fundamentals of machine learning/neural network model and its key concepts. Learning how to use TensorFlow for implementing machine learning algorithms, data preprocessing, supervised learning. Additionally, learners develop skills in evaluating and deploying machine learning models using TensorFlow.
Register for this course and see more details by visiting:
OpenCourser.com/course/9169qg/tensorflow
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What's inside
Syllabus
Project Overview
In this project, you'll embark on an exciting journey of building a machine learning model to classify images of cats and dogs using the power of TensorFlow. This is a beginner project-based course which should take approximately 2 hours to finish.
Image classification is a fundamental problem in computer vision, and with the popularity of deep learning, it has become even more accessible and accurate. From preprocessing a dataset containing labeled images of cats and dogs to dive into building a convolutional neural network (CNN), this project will provide you with insights into the process of building, training, and evaluating a convolutional neural network for image classification, while also giving you a deeper understanding of TensorFlow's capabilities.
Furthermore, you'll explore the importance of hyperparameters such as learning rate, batch size, and the number of epochs and implement techniques like data augmentation and dropout to enhance your model's ability to generalize well to new data. This course is aimed at learners who are looking to get started with their deep learning journey with TensorFlow.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Introduces and teaches basic machine learning and coding principles, suitable for beginners
Instructs on setting up TensorFlow and its basics, a widely used machine learning tool
Provides hands-on practice in building and evaluating a neural network model using TensorFlow
Emphasizes important concepts in machine learning, such as data preprocessing and supervised learning
Focuses on image classification, a fundamental task in computer vision
Provides practical experience in data augmentation and dropout techniques for model enhancement
Save this course
Save TensorFlow for Beginners: Basic Binary Image Classification 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 for Beginners: Basic Binary Image Classification with these
activities:
Review 'Deep Learning for Coders with fastai and PyTorch'
Show steps
This book provides a comprehensive overview of deep learning concepts and techniques, preparing you for the TensorFlow course.
View
Deep Learning for Coders with Fastai and...
on Amazon
Show steps
-
Read Chapters 1-3
-
Complete the exercises in Chapter 3
Follow TensorFlow Tutorials
Show steps
TensorFlow provides official tutorials that can help you build a strong foundation in TensorFlow basics.
Browse courses on
TensorFlow
Show steps
-
Complete the 'Hello World' tutorial
-
Work through the 'MNIST for Beginners' tutorial
Solve TensorFlow Coding Challenges
Show steps
Solving coding challenges will enhance your TensorFlow programming skills and deepen your understanding of the concepts.
Browse courses on
TensorFlow
Show steps
-
Join a TensorFlow coding challenge platform
-
Solve 10 beginner-level challenges
Two other activities
Expand to see all activities and additional details
Show all five activities
Build a Simple Image Classifier
Show steps
Creating your own image classifier will provide hands-on experience and reinforce the course concepts.
Browse courses on
TensorFlow
Show steps
-
Gather a dataset of images
-
Train a convolutional neural network model using TensorFlow
Join a TensorFlow Study Group
Show steps
Engaging in discussions with peers can clarify concepts and enhance your learning experience.
Browse courses on
TensorFlow
Show steps
-
Find a study group or create your own
-
Meet regularly to discuss course topics and work on projects
Review 'Deep Learning for Coders with fastai and PyTorch'
Show steps
This book provides a comprehensive overview of deep learning concepts and techniques, preparing you for the TensorFlow course.
View
Deep Learning for Coders with Fastai and...
on Amazon
Show steps
Show steps
Show steps
- Read Chapters 1-3
- Complete the exercises in Chapter 3
Follow TensorFlow Tutorials
Show steps
TensorFlow provides official tutorials that can help you build a strong foundation in TensorFlow basics.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Complete the 'Hello World' tutorial
- Work through the 'MNIST for Beginners' tutorial
Solve TensorFlow Coding Challenges
Show steps
Solving coding challenges will enhance your TensorFlow programming skills and deepen your understanding of the concepts.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Join a TensorFlow coding challenge platform
- Solve 10 beginner-level challenges
Two other activities
Expand to see all activities and additional details
Show all five activities
Build a Simple Image Classifier
Show steps
Creating your own image classifier will provide hands-on experience and reinforce the course concepts.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Gather a dataset of images
- Train a convolutional neural network model using TensorFlow
Join a TensorFlow Study Group
Show steps
Engaging in discussions with peers can clarify concepts and enhance your learning experience.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Find a study group or create your own
- Meet regularly to discuss course topics and work on projects
Career center
Learners who complete TensorFlow for Beginners: Basic Binary Image Classification will develop knowledge and skills
that may be useful to these careers:
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers use their knowledge of TensorFlow, and other machine learning and deep learning tools, to design and build AI-powered systems. These systems can be used to solve a wide range of problems, including natural language processing, image recognition, and robotics. This course will help someone who wants to become an AI Engineer learn the fundamentals of TensorFlow and how to use it to build AI-powered systems.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers use TensorFlow and other tools to build and maintain the machine learning models that power self-driving cars, facial recognition, personalized shopping recommendations, and fraud detection, to name a few examples. Someone who wants to embark on a career as a Machine Learning Engineer should take this course because it will help them understand the basic principles of machine learning and deep learning, as well as how to use TensorFlow, an industry-leading open-source machine learning library.
Deep Learning Engineer
Deep Learning Engineer
Deep Learning Engineers use TensorFlow and other deep learning tools to build and maintain the deep learning models that power a wide range of applications, such as self-driving cars, facial recognition, and natural language processing. This course would be beneficial for someone who wants to become a Deep Learning Engineer, as it will help them build a strong foundation in TensorFlow and how to use it to build deep learning models.
Data Scientist
Data Scientist
Data Scientists use their knowledge of TensorFlow, and other deep learning tools, to create models that can classify images, such as cancerous cells, cats and dogs, or other objects. By leveraging the capabilities of TensorFlow and computer vision, professionals in this role can enhance diagnostic tools, increase efficiency in manufacturing and logistics, and provide more personalized customer experiences.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers design, develop, and implement computer-based systems that can interpret and understand images and videos. Such systems are used in a wide variety of applications, including self-driving cars, facial recognition, medical imaging, robotics, and more. This course can provide Computer Vision Engineers with a solid foundation in TensorFlow, which will help them develop better performing computer vision systems.
Machine Learning Researcher
Machine Learning Researcher
Machine Learning Researchers use TensorFlow and other machine learning and deep learning tools to conduct research in the field of machine learning. This course can provide Machine Learning Researchers with a solid foundation in TensorFlow, which will help them conduct better research.
Data Analyst
Data Analyst
Data Analysts often work with machine learning and deep learning tools to build and maintain the models that businesses rely on. By adding TensorFlow to their toolbox, a Data Analyst can build more powerful models that can solve a wider range of problems. This course can help someone who wants to become a Data Analyst build a foundation in TensorFlow.
Software Engineer
Software Engineer
Software Engineers who work with machine learning and deep learning often work with TensorFlow. This course would be beneficial for a Software Engineer, especially one who wants to specialize in machine learning, computer vision, or natural language processing, as it teaches the fundamentals of TensorFlow, how to work with image data for classification, and introduces common deep learning techniques like data augmentation and dropout.
Computer Scientist
Computer Scientist
Computer Scientists who work with machine learning and deep learning often use TensorFlow. This course would be beneficial for someone who wants to become a Computer Scientist in this field, as it will help them build a strong foundation in TensorFlow and how to use it to conduct research and develop machine learning and deep learning applications.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use machine learning and deep learning to build models that can predict financial outcomes. TensorFlow is one of the leading tools in this field. This course can help someone who wants to become a Quantitative Analyst learn the fundamentals of TensorFlow and how to use it to build financial models.
Research Scientist
Research Scientist
Research Scientists who work with machine learning and deep learning often use TensorFlow. This course would be beneficial for someone who wants to become a Research Scientist in this field, as it will help them build a strong foundation in TensorFlow and how to use it to conduct research.
Data Engineer
Data Engineer
Data Engineers who work with machine learning and deep learning often use TensorFlow. This course would be beneficial for someone who wants to become a Data Engineer in this field, as it will help them build a strong foundation in TensorFlow and how to use it to work with machine learning and deep learning data.
Software Developer
Software Developer
Software Developers who work with machine learning and deep learning often use TensorFlow. This course would be beneficial for someone who wants to become a Software Developer in this field, as it will help them build a strong foundation in TensorFlow and how to use it to develop machine learning and deep learning applications.
Product Manager
Product Manager
Product Managers who work with machine learning and AI products may benefit from this course, as it will help them build a foundation in TensorFlow and machine learning concepts.
Business Analyst
Business Analyst
Business Analysts who need to work with machine learning and data science teams may need to understand the basics of TensorFlow. This course can help build those foundational elements.
For more career information including salaries, visit:
OpenCourser.com/course/9169qg/tensorflow
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
TensorFlow for Beginners: Basic Binary Image Classification.
Provides a comprehensive overview of deep learning techniques and their applications in computer vision, natural language processing, and other domains.
Focuses on applying deep learning techniques to computer vision tasks such as image classification, object detection, and image segmentation.
Provides practical guidance on building and deploying machine learning models using popular Python libraries such as Scikit-Learn, Keras, and TensorFlow.
Offers a hands-on approach to machine learning, covering topics such as data preparation, feature engineering, and model evaluation.
Provides a comprehensive overview of deep learning techniques using the R programming language.
Provides a comprehensive overview of deep learning architectures and their applications in artificial intelligence.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/9169qg/tensorflow
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Effort
90 minutes
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Soumava Dey
Language
English
Good to know
Introduces and teaches basic machine learning and coding principles, suitable for beginners
Instructs on setting up TensorFlow and its basics, a widely used machine learning tool
Provides hands-on practice in building and evaluating a neural network model using TensorFlow
Emphasizes important concepts in machine learning, such as data preprocessing and supervised learning
Focuses on image classification, a fundamental task in computer vision
Provides practical experience in data augmentation and dropout techniques for model enhancement
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