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Updated in [August 31st, 2023]

What does this course tell?
(Please note that the following overview content is from Alison)
TensorFlow Tutorial 1 - Installation and setup Deep Learning Environment (Anaconda and PyCharm) TensorFlow tutorial 2 - Tensor Basics Tensor Flow Tutorial 3 - Convolutional Neural Networks with Sequential and Functional API TensorFlow Tutorial 4 - Adding Regularization with L2 and Dropout T TensorFlow tutorial 5 - RNNs GRUs LSTMs and Bidirectionality

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?
Through this course, learners will acquire skills and knowledge in installing and setting up a deep learning environment (Anaconda and PyCharm), understanding the basics of TensorFlow, building convolutional neural networks with the Sequential and Functional API, adding regularization with L2 and Dropout, and constructing RNNs, GRUs, LSTMs, and Bidirectionality.
lHow does this course contribute to professional growth?
This course provides a comprehensive introduction to TensorFlow, a powerful open source library for deep learning. It covers the basics of TensorFlow, including installation and setup of an Anaconda and PyCharm environment, as well as tutorials on Tensor Basics, Convolutional Neural Networks, Regularization with L2 and Dropout, and Recurrent Neural Networks (GRUs, LSTMs, and Bidirectionality). By taking this course, professionals can gain a better understanding of the fundamentals of TensorFlow and how to use it to create powerful deep learning models. This course can help professionals to stay up-to-date with the latest advancements in deep learning and to develop their skills in this rapidly growing field.

Is this course suitable for preparing further education?
Yes, the TensorFlow 20 Beginner Tutorials course is suitable for preparing further education. It covers topics such as installation and setup of a deep learning environment, Tensor basics, convolutional neural networks, regularization with L2 and Dropout, and RNNs GRUs LSTMs and Bidirectionality.