Jose Portilla
This course will guide you through how to use Google’s latest TensorFlow 2 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 2 framework in a way that is easy to understand.
We’ll focus on understanding the latest updates to TensorFlow and leveraging the Keras API (TensorFlow 2.0’s official API) to quickly and easily build models. In this course we will build models to forecast future price homes, classify medical images, predict future sales data, generate complete new text artificially and much more!
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
NumPy Crash Course
Pandas Data Analysis Crash Course
Data Visualization Crash Course
Neural Network Basics
TensorFlow Basics
Keras Syntax Basics
Artificial Neural Networks
Densely Connected Networks
Convolutional Neural Networks
Recurrent Neural Networks
AutoEncoders
GANs – Generative Adversarial Networks
Deploying TensorFlow into Production
and much more!
Keras, a user–friendly API standard for machine learning, will be the central high–level API used to build and train models. The Keras API makes it easy to get started with TensorFlow 2. Importantly, Keras provides several model–building APIs (Sequential, Functional, and Subclassing), so you can choose the right level of abstraction for your project. TensorFlow’s implementation contains enhancements including eager execution, for immediate iteration and intuitive debugging, and tf.data, for building scalable input pipelines.
Instructor Details
Courses : 21
Specification: Complete Tensorflow 2 and Keras Deep Learning Bootcamp
|
40 reviews for Complete Tensorflow 2 and Keras Deep Learning Bootcamp
Add a review
| Price | $17.99 |
|---|---|
| Provider | |
| Duration | 19 hours |
| Year | 2022 |
| Level | All |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
$17.99
Marco Antonio Hernandez –
clear explanations. Useful code and exercises
Aquib Ehtesham –
video is getting pause many times
Ammar Naser –
excellent
Vinod Kumar –
Wonderful course, precise to the point. Loved it. Thanks!
Vi Ly –
I think it is useful for my shool
Thiyagarajan Paramadayalan –
the instructor was very clearly communicating
Teo Jun Yan Jonathan –
It was great, easy to follow the tutorials
Siavash Saki –
Amazing Course. I learned so much. The concepts are explained very easy so that everybody can understand them. Jose makes Neural Networks and Deep Learning a piece of cake for you. Highly Recommended!
Ishaan Das –
The pacing on the course is amazing. I really like the short tests that challenge your understanding. I’m starting section 5 so I’ll update this review once I have been through section 7.
Elio Jordan Lopes –
Constructively explained by the mentor. You’re making good content and imparting great knowledge Mr. Jose!
Rangga Putra Pertama –
yes
Jorge Luis Lopez Grisman –
f
Anya Linley –
I took this course straight after Jose’s Python for Data Science and Machine Learning Bootcamp. This is a great follow on course which provides a nice introduction to TensorFlow with examples of various different types of neural network. Having taken this course, I feel ready to adapt these examples to my own needs. I’ve gained a high level understanding of how neural networks work and now have a starting point from which to work. Jose is very clear and engaging in his teaching and he responds quickly to any questions. Just don’t expect to be an expert at the end of the course since this is a HUGE topic. Happy learning!
Francesco Fumagalli –
I come from Jose Portilla’s Python for Data Science and Machine Learning Bootcamp, so the first 7 parts were just a revision for me: I mostly skipped them jumping right to the exercise part, only going back in case I had forgotten something. And I had no prior web development knowledge, so I also just skimmed over the last part about Deployment. Despite the fact that this couse only provided 9 effective hours of contents, what content it was! It gives a way more in depth look on more modern Neural Networks, teaching you how to build Convolutional Neural Networks (for Image Recognition, for example), Recurring NNs (for time series predictions, including sales forecast, and a model that generates text in the style of Shakespeare), AutoEncoders (for Noise Removal and Compression) and Generative Adversary Networks (Networks that learn how to generate images similar to the ones you feed them). What a great course! My only complaint would be that at times it goes a bit too fast for me to follow, so I had to either stop the video while catching up or reduce the playback speed to 0.75x or 0.5x. But that’s a minor issue: I’ve learnt a lot, now I think I’ll spend some time trying to implement what I’ve learnt before jumping into another course, because it’s a lot of stuff and has to be properly digested. Thank you Jose, great course!
Sid –
Amazing Course!
Koushyar Rajavi –
I am taking this course after taking Python for Data Science and Machine Learning Bootcamp which I thoroughly enjoyed. The course is very similar to the previous course I took. Jose carefully goes through the topics with several examples and then there are very useful exercises that are helpful in better understanding the topics. So far I have enjoyed the course and hope that it continues in the same manner.
Theophilus Siameh –
I don’t see anything new in this course from your previous tensorflow course except the deployment section (13)
Johnny Diocena –
intuitive
Olivia Mizumura –
The instructor, Jose, is extremely clear in his delivery of the concepts. He makes difficult and abstract ideas easy to understand, even for someone with little background in the field.
Petja –
Perfekt!
Mostafa Elsaadouny –
Thanks a lot for this amazing content and simple explanation. One of the best courses for deep learning.
Mario Roberto Martinez –
Great setup video! I found it helpful.
Yuri Turygin –
so far so good.
Munum Butt –
Excellent course as usual, highly detailed and comprehensive
Shubhendra Kumar –
The course was very good especially from the perspective of trying hands on practical use cases of tensorflow 2.0 and keras. Must do course for people aiming to develop the foundational and conceptual platform of deep learning modelling involving application on real world implementation techniques. However slight improvement on theoretical explanation and implementation in sections on RNN and GANs could have made. Overall a good to do course.
Ronaka Roy Khatri –
Great course. Very simplified.
Luka Kujundzic Lujan –
great course especially if you grab it on discount(which is quite often), but some former knowledge is recommended. Also if you get stuck on something, be ready to watch same lecture again, to google problems from other sources or even check other courses. (ha what do you think that you will learn ML/DL with just 1 course 🙂 🙂
B. Sumanth Kumar –
it is good course to learn Tensorflow and python libraries. It definitely enhances our skills in using Tensorflow
Francisco Massucci Silveira –
Jose Portilla, as usual, delivering great content and amazing courses. This is especially well done, with complex subjects being divided into small, understandable topics.
Mel Awasi –
Excellent. Jose is the best!
Yosh Noro –
Instructor is very competent. I wish if the explanations for the commands were a bit more deeper, and perhaps some tips on where to go to find more information.
Sungbok Lee –
Nice explanation makes me easy to understand the content.
Debora B. S. Paulo –
ser em portugu s
Kishan Grewal –
Yes, I want to learn machine learning and this course is helping me
Tian Jie –
I have gone through several courses taught by Jose the way he explain complex concepts in simple words really help me to learn and enhance my knowledge in respective domains. Looking forward to the learnings for the deep learning moving forward.
Chandrodoy Pal –
Could be better if GAN could be implemented on different dataset as GAN on MNIST dataset is vey common and it is easily available everywhere.
Liverios Papantoniou –
Jose is a great teacher, that is why I have taken some of his courses. He also escalates the subjects really well reaching a point where you have to search on your own to acquire greater knowledge, exactly as should be expected by online courses.
Jonathan Lazzaro –
Great deep learning course! It covers a wide variety of key topics in an easy to follow manner. The NumPy, Pandas, and Seaborn crash courses were also very beneficial.
Dr. Umesh Dutta –
Good course.
Masiyandaita Majange –
Great course with clear explanations of theory and good coding practice. I don’t know web development but the Deployment section sparked my curiosity!