Machine Learning With TensorFlow: The Practical Guide
Ready to dive into Machine Learning with TensorFlow? Join us in the practical journey of mastering machine learning techniques and building real-world applications. #MachineLearning #TensorFlow #AIEducation ▼
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Course Feature
Cost:
Paid
Provider:
Udemy
Certificate:
Paid Certification
Language:
English
Start Date:
2019-01-09
Course Overview
❗The content presented here is sourced directly from Udemy 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)
This course covers all aspects of next-generation machine learning with Tensorflow, an open source library developed by Google. It includes fundamentals of Tensorflow, installation on Windows, Mac and Linux, basics of machine learning and its types, algorithms such as linear regression, logistic regression, NN regression, K-Means algorithm, neural networks, convolution neural networks, recurrent neural networks, and more. It also provides quizzes and a project on Deep Neural Networks using Tensorflow to ensure correct implementation. Start now and learn all about machine learning with Tensorflow.
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 this course, learners will acquire knowledge and skills in Tensorflow fundamentals and installation, details about tensors, operators, variables and others, details about machine learning inference and its types, different algorithms such as linear regression, logistic regression, clustering, K-means algorithm, kernels and many more, various advanced learning networks and its implementation such as neural networks, convolution neural networks, recurrent neural networks, and a project on deep neural networks using Tensorflow. Additionally, learners will be able to test their understanding of the topics with quizzes provided at the end of each section.
lHow does this course contribute to professional growth?
This course on Machine Learning with TensorFlow: The Practical Guide provides professionals with the opportunity to gain a comprehensive understanding of the fundamentals of machine learning and its implementation using TensorFlow. It covers topics such as TensorFlow fundamentals and installation, details about tensors, operators, variables, and more, as well as machine learning inference and its types. Additionally, it provides an in-depth look into different algorithms such as linear regression, logistic regression, clustering, K-means algorithm, kernels, and more. Furthermore, it covers advanced learning networks such as neural networks, convolution neural networks, recurrent neural networks, and more. With quizzes at the end of each section and a project on deep neural networks using TensorFlow, this course provides a comprehensive and valuable learning experience for professionals looking to expand their knowledge and skills in machine learning.
Is this course suitable for preparing further education?
Yes, this course is suitable for preparing further education as it covers all the basics of Tensorflow, machine learning, and its types, as well as advanced machine learning topics such as neural networks, convolution neural networks, recurrent neural networks, and more. It also includes quizzes and a project on deep neural networks using Tensorflow to ensure correct implementation.
Course Syllabus
Introduction
Getting started with Tensorflow
Tensorflow Basics
Machine Learning Basics
Main Algorithms
Advance ML
Course Provider
Provider Udemy's Stats at AZClass
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