Total TensorFlow Guide: Deep Learning with Python Course
What you’ll learn
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Understand how Neural Networks Work
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Build your own Neural Network from Scratch with Python
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Use TensorFlow for Classification and Regression Tasks
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Use TensorFlow for Image Classification with Convolutional Neural Networks
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Use TensorFlow for Time Series Analysis with Recurrent Neural Networks
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Use TensorFlow for solving Unsupervised Learning Problems with AutoEncoders
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Learn how to conduct Reinforcement Learning with OpenAI Gym
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Create Generative Adversarial Networks with TensorFlow
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Become a Deep Learning Guru!
Welcome to the Complete Guide to TensorFlow for Deep Learning with Python!
This course will guide you through how to use Google’s TensorFlow framework to create artificial neural networks for deep learning! This course aims to give you an easy to understand guide to the complexities of Google’s TensorFlow framework in a way that is easy to understand. Other courses and tutorials have tended to stay away from pure tensorflow and instead use abstractions that give the user less control. Here we present a course that finally serves as a complete guide to using the TensorFlow framework as intended, while showing you the latest techniques available in deep learning!
This course is designed to balance theory and practical implementation, with complete jupyter notebook guides of code and easy to reference slides and notes. We also have plenty of exercises to test your new skills along the way!
This course covers a variety of topics, including
- Neural Network Basics
- TensorFlow Basics
- Artificial Neural Networks
- Densely Connected Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- AutoEncoders
- Reinforcement Learning
- OpenAI Gym
- and much more!
There are many Deep Learning Frameworks out there, so why use TensorFlow?
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google’s Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.
It is used by major companies all over the world, including Airbnb, Ebay, Dropbox, Snapchat, Twitter, Uber, SAP, Qualcomm, IBM, Intel, and of course, Google!
Become a machine learning guru today! We’ll see you inside the course!
Who this course is for:
- Python students eager to learn the latest Deep Learning Techniques with TensorFlow
12 reviews for Total TensorFlow Guide: Deep Learning with Python Course
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Original price was: $119.99.$19.99Current price is: $19.99.
Hans Palacios –
Overall, great overview and examples to work with! The lessons are explained at a good pace and in enough detail to successfully complete each of the projects. There were some variations needed along the way to adapt the use of TensorFlow, but with some quick searches in Stack Overflow, they were all resolved without issue for me. I’m looking forward to continuing learning from Jose through his other courses, particularly the one delving into TensorFlow 2. Keep up the great work!
João Pedro Oliveira Batisteli –
Muito bom, os exercícios ajudaram muito a aprender o funcionamento da biblioteca
Stanley Koziol –
some important details in video python lectures are not explained at all (for example -1 parameters etc.). It would really help if the python steps of building the network were visualized by picture
David Farkash –
It was a good match for me since it gives the practical aspects of ML and a vast view of TensorFlow capabilities
Pankaj Kumar Shaw –
Everything is perfect. Need lil more explanation behind coding
Michael Smith –
Outdated, significantly. Explanations were kind of hand wavy.
Farid J. Nejad –
The material is old.
Justin –
Brilliant from start to finish. Thank you for making education so accessible.
Steven Zajac-Descoteaux –
Just issues with setting up the libraries for TF 1. The file given doesn’t really work. Had to do so manually and took a VERY VERY long time… but did work eventually
Kanimozhi Kalaichelvan –
Great course for beginners of Tensorflow 🙂
Michael Virnelson –
the code is now very outdated and the functions do not work in current codes
Ricky Wong –
Old version of tensorflow.