❗The content presented here is sourced directly from Grow with Google platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [August 31st, 2023]
What does this course tell?
(Please note that the following overview content is from Alison)
A self-study guide for aspiring machine learning practitioners Machine Learning Crash Course features a series of lessons with video lectures real-world case studies and hands-on practice exercises
Some of the questions answered in this course:
Learn best practices from Google experts on key machine learning concepts
How does machine learning differ from traditional programming?
What is loss and how do I measure it?
How does gradient descent work?
How do I determine whether my model is effective?
How do I represent my data so that a program can learn from it?
How do I build a deep neural network?
We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
What skills and knowledge will you acquire during this course?
By taking the Machine Learning Crash Course with TensorFlow APIs, learners will acquire knowledge and skills in key machine learning concepts, such as loss, gradient descent, model effectiveness, data representation, and deep neural networks. They will also learn best practices from Google experts on these topics.
lHow does this course contribute to professional growth?
This course provides professional growth by teaching aspiring machine learning practitioners best practices from Google experts on key machine learning concepts. It covers topics such as how machine learning differs from traditional programming, how to measure loss, how gradient descent works, how to determine whether a model is effective, how to represent data so that a program can learn from it, and how to build a deep neural network. Through video lectures, real-world case studies, and hands-on practice exercises, this course provides a comprehensive guide to mastering machine learning with TensorFlow APIs.
Is this course suitable for preparing further education?
The Machine Learning Crash Course with TensorFlow APIs is a self-study guide for aspiring machine learning practitioners. It features a series of lessons with video lectures, real-world case studies, and hands-on practice exercises. It covers best practices from Google experts on key machine learning concepts, such as how machine learning differs from traditional programming, how to measure loss, how gradient descent works, how to determine whether a model is effective, how to represent data so that a program can learn from it, and how to build a deep neural network. This course is suitable for preparing further education in machine learning.
