Complete Tensorflow 2 and Keras Deep Learning Bootcamp

Learn to use Python for Deep Learning with Google's latest Tensorflow 2 library and Keras!

4.67 (8190 reviews)

Udemy

platform

English

language

Data Science

What you will learn

Learn to use TensorFlow 2.0 for Deep Learning

Leverage the Keras API to quickly build models that run on Tensorflow 2

Perform Image Classification with Convolutional Neural Networks

Use Deep Learning for medical imaging

Forecast Time Series data with Recurrent Neural Networks

Use Generative Adversarial Networks (GANs) to generate images

Use deep learning for style transfer

Generate text with RNNs and Natural Language Processing

Serve Tensorflow Models through an API

Use GPUs for accelerated deep learning

Why take this course?

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.

TensorFlow 2 makes it easy to take new ideas from concept to code, and from model to publication. TensorFlow 2.0 incorporates a number of features that enables the definition and training of state of the art models without sacrificing speed or performance

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 deep learning guru today! We'll see you inside the course!

Screenshots

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Reviews

Ravi

April 14, 2024

The stepwise approach to simplifying the complex concepts of Machine Learning not only enhances the appeal of this course but also makes it truly remarkable. The real-life examples used to elucidate various machine learning models seamlessly integrate theory with practical applications, fostering a deeper understanding and facilitating their utilization across a wide array of use cases.

Wim

March 22, 2024

The course is clearly structured, the explanation goes into solid detail, and the presenter is clearly understandable and is not wasting time writing a whole book of comments in the code. The section about NLP could be larger though, since that was the only section where I had the feeling that we went through the section without going into too much detail. Otherwise, great course!

Jessica

March 19, 2024

Jose Portilla is my favorite Udemy instructor. I always choose his courses if they are available for a topic. Great pace, great theory and practical coverage, and easy to understand and follow.

Rene

March 15, 2024

Exactly what I needed. It was easy to fit the entire course into the few rare moments, I can spare in the daily routine, and still I was never stuck. As an introduction for people like me who has almost no foothold in AI, and merely want to get started, this is great. Sometimes the focus on pandas and data preprocessing goes a little overboard, but at the end of the day, I'm happy about every piece of numpy, scikit, pandas, seaborn, keras etc. that was touched upon. Some of the api seem to have changed since 2019, but that was a good chance to dig into some keras problem solving. All issues could be solved. Oddly enough though, I seldom could match the results exactly, probably due to changes in tensorflow over the years. Great beginners course, thumbs up.

Jennifer

February 29, 2024

This instructor's approach to some very technical topics is so well done. It's not like listening to a lecture, but rather like being told a story and knowing the ending will be great. Thank you!

Ola

February 7, 2024

Jose Portilla's Pierian data is the best. I took his machine learning course and I'm back for his deep learning. He has an incredible way of combining basic applied theoretical concepts with code implementation.

Azaria

December 19, 2023

Very detailed and useful course. Plenty of external work and problem solving to get stuck into. Very long course, though I suppose that's necessary to get through the volume of material.

LUIS

December 16, 2023

Excellent course if you are a beginner in deep learning, just like me. No more than a week and I was able to build my own deep learning models. The teacher also gives a good explanation of basic concepts (loss functions, overfitting, etc.) and these are reinforced every lesson. However, I wish he had spent more time on hyperparameter searching. In my case, I had a problem while I was training my first image classifier. The loss got stuck and my model was performing no better than a random classifier, and after a few days of searching hyperparameters, a smaller learning rate solved the problem. Perhaps an algorithmic searching could had helped me.

Nuthakki

December 16, 2023

Few Math and statistics concepts used behind the machine learning algorithms are not properly explained for a beginner to understand. Those explanations are not intuitive. I kept referring other sources to get an understanding about those concepts. Keeping that aside, rest of the course is excellent.

Max

December 11, 2023

This course is great so far. I have taken Mr. Portilla's Udemy classes before, and I have always been impressed. I look forward to completing this course.

Yesudian

November 22, 2023

This is an excellent course. It covers from the basics to the details of what I expected out. It contains suitable references where I need to go deep.

Jelmer

November 11, 2023

This course was really a nice steady, decent Jose-course. Much learned, much enjoyed. Positives: Tempo, content (depth and breadth), enthusiasm, relevance Negatives: Volume (and its quality) varied somewhat between video's, not up-to-date with newer TensorFlow versions (see below), most of my own run models had vanishing gradients after typing along (and really, really quintuply checking that no typo's and errors are present), previous problem persisted in the notebooks where no typo's of my side could possibly be present Suggestions: The version should be specified in the course name: TensorFlow 2.0, because newer versions have a very different syntax and many examples turned out to be incompatible to newer versions that I tried running at first, assuming forward compatibility of the examples. Also, it would be good if this warning would be provided at the beginning of the course, since that might save quite a bit of time.

Ian

November 6, 2023

Locally installing Python/Tensorflow doesn't work, even if I install all of the exact same versions of everything. This course needs to stay up to date or just commit to using colab.

Stan

October 30, 2023

This course is amazing. It gave me a good solid foundation inthe theory and practice of basic neural networks, and the deployment session was an unexpected bonus. I now feel prepared to go forth and build and deploy an application to meet my specific needs. I realize that I have been exposed to only the basic commands and options, but I learned how to think may way around neural modelling and I know where to find the documentation. One suggestion. I ran into frustration running the course examples because of version mismatches and I can see from the Q&A that I'm not alone. I suggest you provide a dockerized version jupyter notebook including all the course requirements (numpy, tensorflow, flask, etc) and post it in dockerhub. Thanks again for this most informative and comprehensive course!

Prasanta

October 18, 2023

Jose is my go to instructor for anything related to Data Science courses. If I need to learn something new in Data Science space , I look for Jose's course first. I have taken many of his courses and I enjoyed each of them. His teaching abilities are great. Course contents are very structure and right for non-technical person. His courses have right mix of theory and practical. His delivery is very clear and at right pace. I learnt a lot from his courses considering I am not a technical person. Like All other courses I enjoyed and learnt a lot from this course as well. I wish to see some Quantum courses from him.

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