A Complete Guide on TensorFlow 2.0 using Keras API
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Welcome to Tensorflow 2.0!
TensorFlow 2.0 has just been released, and it introduced many features that simplify the model development and maintenance processes. From the educational side, it boosts people’s understanding by simplifying many complex concepts. From the industry point of view, models are much easier to understand, maintain, and develop.
Deep Learning is one of the fastest growing areas of Artificial Intelligence. In the past few years, we have proven that Deep Learning models, even the simplest ones, can solve very hard and complex tasks. Now, that the buzz–word period of Deep Learning has, partially, passed, people are releasing its power and potential for their product improvements.
The course is structured in a way to cover all topics from neural network modeling and training to put it in production.
In Part 1 of the course, you will learn about the technology stack that we will use throughout the course (Section 1) and the TensorFlow 2.0 library basics and syntax (Section 2).
In Part 2 of the course, we will dig into the exciting world of deep learning. Through this part of the course, you will implement several types of neural networks (Fully Connected Neural Network (Section 3), Convolutional Neural Network (Section 4), Recurrent Neural Network (Section 5)). At the end of this part, Section 6, you will learn and build their own Transfer Learning application that achieves state of the art (SOTA) results on the Dogs vs. Cats dataset.
Courses : 8
Specification: A Complete Guide on TensorFlow 2.0 using Keras API
18 reviews for A Complete Guide on TensorFlow 2.0 using Keras API
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Yasser Aoujil –
The part where Q DL is applied is poorly explained, the instructor should use examples just like in theory part. Overall course is good.
Andrew Zou –
I would like to know more about the new features which are applicable in the exercises.
Jeff Dean –
Great combo of theory and practice. Really easy to do labs on colab. Great level of depth on the theory.
Jayant Phate –
Excellent introduction, got complete idea about the course.
James Crosbie –
Some useful items explaining tf2. But repetative at at later sections where rebuilding models from earlier sections and skips through section topics on tf lite and tf serving where it needs more depth
Atul Gupta –
Great Course … Enjoying
Deepanjan Saha –
Very good and simple explaination of all the topics.
Example scripts return errors when I try to run them
Harish Patil –
This course is really well designed to cover all the required topics of tensorflow. I felt a few sections have been wrapped in very short manner, especially in TFDV, TFT, TFLite, Distributed training. These sessions could be explained better
Reza Tasooji –
It is OK course but you can find better than this. There are not enough explanations in examples, the section for RL is quite useless. No information is provided and the example of AI trade is poorly explained, the instructor just write lines of code, no comment no description. The RNN example in the course is not useful too. Overall not enough explanations and the comment section has no answer although the instructor keep saying posting your questions.
Ashish Vishwakarma –
Overall course structure and content is good. Kiril has taught intuition very well. Code explanation by hadelin is as always superb. Rest of the section should have been taught by hadelin himself. Other guy has disappointed. Could not myself from highlighting this here. Hoping that in the updated version, hadelin will take the rest of the sections.
Anshuman Goswami –
Its great but I didn’t catch your name.
Sepehr Eftekharian –
the course is great. the challenge is the author speaks so fast.
Ananya Pandey –
This is first section first video it appears appealing. a lot of things to learn i think.
Sagar Sheth –
The course covers major broad topics to trigger further learning. Some new examples aprt from regular fashion MNIST etc could have been more engaging. In any case this is a good introduction learning
Karavadi Ravi Teja –
GOOD WITH NICE EXPLANATION
James Esquivel –
Sita Rami Reddy Lankireddy –
not able to run colab notebooks