The Complete Guide to TensorFlow 1x
This comprehensive course will teach you the fundamentals of TensorFlow 1x, so you can confidently build and deploy powerful machine learning models with ease. ▼
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Course Feature
Cost:
Paid
Provider:
Udemy
Certificate:
Paid Certification
Language:
English
Start Date:
2017-08-22
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 is designed to help data analysts, data scientists, and researchers increase the speed and efficiency of their machine learning activities. It covers the use of Google's TensorFlow, which has over 6000 open source repositories and has been used for voice and sound recognition, language translation, face recognition, early detection of skin cancer, and preventing blindness in diabetics. The course includes an introduction to machine learning and deep learning, techniques such as clustering, linear regression, and logistic regression, reinforcement learning, Q-learning algorithm, OpenAI Gym framework, neural networks, GPU computing, multimedia programming, and deep learning on Android. It is authored by Rodolfo Bonnin, Giancarlo Zaccone, Md Rezaul Karim, and Ahmed Menshawy.
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 the end of this course, learners will have acquired a solid knowledge of the all-new TensorFlow and be able to implement it efficiently in production. Learners will have explored the main features and capabilities of TensorFlow such as a computation graph, data model, programming model, and TensorBoard. They will have learned the different techniques of machine learning such as clustering, linear regression, and logistic regression with the help of real-world projects and examples. Learners will have also learned the concepts of reinforcement learning, the Q-learning algorithm, and the OpenAI Gym framework. Additionally, they will have gained an understanding of neural networks and seen how convolution, recurrent, and deep neural networks work and the main operation types used in building them. Furthermore, learners will have acquired advanced concepts such as GPU computing and multimedia programming. Finally, they will have seen an example of deep learning on Android using TensorFlow.
lHow does this course contribute to professional growth?
This course contributes to professional growth by providing a comprehensive guide to TensorFlow 1x. It covers the main features and capabilities of TensorFlow, such as a computation graph, data model, programming model, and TensorBoard. It also teaches different techniques of machine learning, such as clustering, linear regression, and logistic regression, with the help of real-world projects and examples. Additionally, the course covers advanced concepts such as GPU computing and multimedia programming, and provides an example of deep learning on Android using TensorFlow. By the end of the course, learners will have a solid knowledge of the all-new TensorFlow and be able to implement it efficiently in production.
Is this course suitable for preparing further education?
This course is suitable for preparing further education as it provides a comprehensive guide to TensorFlow 1x, covering topics such as machine learning, deep learning, neural networks, GPU computing, and multimedia programming. It also includes real-world projects and examples, and is authored by experienced professionals in the field.
Course Syllabus
Getting Started with Machine Learning and Deep Learning
First Look at TensorFlow
Exploring and Transforming Data
Clustering
Linear Regression
Logistic Regression
Reinforcement Learning
Simple Feed-Forward Neural Networks
Convolutional Neural Networks
Autoencoders
Recurrent Neural Networks
Deep Neural Networks
GPU Computing
Advanced TensorFlow Programming
Advanced Multimedia Programming with TensorFlow
Course Provider
Provider Udemy's Stats at AZClass
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