Complete Guide to TensorFlow for Deep Learning with Python
Learn how to use Google's Deep Learning Framework - TensorFlow with Python! Solve problems with cutting edge techniques!
4.48 (17014 reviews)
98 151
students
14 hours
content
Apr 2020
last update
$94.99
regular price
What you will learn
Understand how Neural Networks Work
Build your own Neural Network from Scratch with Python
Use TensorFlow for Classification and Regression Tasks
Use TensorFlow for Image Classification with Convolutional Neural Networks
Use TensorFlow for Time Series Analysis with Recurrent Neural Networks
Use TensorFlow for solving Unsupervised Learning Problems with AutoEncoders
Learn how to conduct Reinforcement Learning with OpenAI Gym
Create Generative Adversarial Networks with TensorFlow
Become a Deep Learning Guru!
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Comidoc Review
Our Verdict
The Complete Guide to TensorFlow for Deep Learning with Python course is an ideal starting point for those interested in deep learning and TensorFlow. Despite its age, the course provides comprehensive coverage of various deep learning techniques using TensorFlow 1.x. However, ensure that you can work around setting up the outdated environment and the transition to TensorFlow 2.x. While there is room for improvement concerning code explanation and theoretical foundation discussions, this course still proves valuable for those eager to delve into deep learning concepts with Python.
What We Liked
- Covers a wide range of topics and deep learning techniques using TensorFlow
- Clear explanations of concepts with real-world examples and projects
- Instructor is knowledgeable and takes time to walk through the examples
- Valuable for those interested in starting their journey in deep learning
Potential Drawbacks
- Some users faced challenges setting up the environment, particularly with newer TensorFlow versions
- Outdated content as it still uses TensorFlow 1.x, which is not fully compatible with 2.x or higher
- Instructor sometimes reads the code without thoroughly explaining each line
- Pacing can be too fast for some learners who need a more detailed explanation of underlying theory
Related Topics
1326292
udemy ID
20/08/2017
course created date
08/08/2019
course indexed date
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