Dr. Ryan Ahmed, Ph.D., MBA
Google has recently released TensorFlow 2.0 which is Google’s most powerful open source platform to build and deploy AI models in practice. Tensorflow 2.0 release is a huge win for AI developers and enthusiast since it enabled the development of super advanced AI techniques in a much easier and faster way.
The purpose of this course is to provide students with practical knowledge of building, training, testing and deploying Advanced Artificial Neural Networks and Deep Learning models using TensorFlow 2.0 and Google Colab. This course will cover advanced, state–of–the–art AI models implementation in TensorFlow 2.0 such as DeepDream, AutoEncoders, Generative Adversarial Networks (GANs), Transfer Learning using TensorFlow Hub, Long Short Term Memory (LSTM) Recurrent Neural Networks and many more. The applications of these advanced AI models are endless including new realistic human photographs generation, text translation, image de–noising, image compression, text–to–image translation, image segmentation, and image captioning.
The global AI and machine learning technology sectors are expected to grow from $1.4B to $8.8B by 2022 and it is predicted that AI tech sector will create around 2.3 million jobs by 2020. The technology is progressing at a massive scale and being adopted in almost every sector. The course provides students with practical hands–on experience in training Advanced Artificial Neural Networks using real–world dataset using TensorFlow 2.0 and Google Colab. This course covers several technique in a practical manner, the projects include but not limited to:
Instructor Details
Courses : 10
Specification: TensorFlow 2.0 Practical Advanced
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15 reviews for TensorFlow 2.0 Practical Advanced
Add a review
| Price | $17.99 |
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| Provider | |
| Duration | 12.5 hours |
| Year | 2021 |
| Level | All |
| Language | English |
| Certificate | Yes |
| Quizzes | No |
$17.99
Tito Mitra –
Seems the trainer has no knowledge of RNN at all. ZERO legitimate explanation of RNN. Almost all the material are copied and just recites the codes.
YSPark –
All through the course, instructor just shows the pre written code, without showing whole process of writing code . Except this, Overall It’s Good course for learn Tensorflow Deep Learning .
Angus Lou –
Very practical, real life, and tactical techniques for TF 2.0. Strongly recommend to those who want to take TF 2.0 into their real cases.
Johan Genis –
Support is not up to standard.
Samuel Cuscovitch –
Yes. Some concepts were a bit of a stretch given not having been grounded is certain fundamentals.
Chris Morris –
I like the review of the linear algebra and derivatives. He explained it very well, and it’s important in understanding machine learning concepts
Raunaq Badjatia –
The instructor did little to explain the more complicated parts of the course material. He stuck to repeating the low hanging fruit. For example, the way he just rushed through the code of RNNs was disappointing. For things like GANs, I actually found it more useful to use Tensorflow’s documentation (from which he has heavily borrowed) and use some internet searches to get some clarification to learn.
Jimmy McInerney –
Clear and easy to understand
Avnish –
The course just demos the existing tutorials available The course should have taken a real world use case and taken through rather than just using mnist samples
Aman Singh –
If the course would have explained about the data preprocessing for csvs with names, numerical, categorical data and then pass it to the keras model then it would have been great. Plus there should be a 2 3 examples of the core tensorflow(tf.nn) instead of tf.keras as it was advanced tensorflow 2.0. Over all i like the way instructor explains the steps and code
John Joachim –
Sound quality and content editing was fairly poor, and two of the Projects even failed for the the Instructor! I am surprised he was so unaware of the concepts of correction and subsequent playback of Recorded Lectures, and I don’t believe I’m being unreasonable to point this out or expect better. I would have chosen different Projects to acquaint one with TensorFlow 2 (nearly everything here is covered more adequately by the TF online documentation). Most frustrating of all was the Instructor’s penchant to keep reviewing preliminary Machine Learning details, while other selective details were not elaborated upon and dismissed as fairly introductory concepts (when they really were not). With each accumulative Project, I became less convinced the Instructor was familiar with the topic and the code. Just my opinion, but that’s how it was presented, overall.
Durga Sandeep –
I already know many concepts from TensorFlow 2.0 Practical. I am looking for a few more advanced and hands on, instead of theory and repetitive lectures. This needs to be addressed. Yeah, some concepts are pretty advanced and they are well taught.
Chandra Shekhar Pandey –
Every thing is being explained in a short and simple manner which makes complex things easy to understand.
Edwin Tan Pei Ming –
Truly excellent! Enjoying every minute of this learning experience! Prof Ryan, will u be coming out with PyTorch Practical and PyTorch Practical Advanced? Hope to learn all these useful skills from u
Kiran Suryakant Chaudhari –
Nice course. Recommended for everyone.