Complete Tensorflow 2 and Keras Deep Learning Bootcamp from Udemy

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.

What's inside

Learning objectives

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

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

Syllabus

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Course Overview

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Teaches TensorFlow 2, which is the latest version and industry standard for deep learning

Develops foundation for TensorFlow 2.0 and Keras API, which are key tools for deep learning

Features thorough explanations, exercises, and code notebooks for practical learning

Focuses on real-world applications through case studies, enabling learners to see practical applications of deep learning

Taught by industry-recognized instructors, José Portilla, who has extensive experience in deep learning and AI

Leverages user-friendly Keras API, making it accessible to learners of different skill levels

Reviews summary

Practical tensorflow 2 & keras deep learning

According to students, this is a highly practical and effective bootcamp for learning TensorFlow 2 and Keras deep learning. Learners consistently praise the instructor's clear explanations and the course's hands-on approach, with many appreciating the well-designed Jupyter notebooks and projects. It's considered an excellent starting point for those new to TF2, building a solid foundation even from basic Python prerequisites. While the course provides comprehensive coverage of various deep learning models, some learners with prior experience felt that initial sections on Python basics were too slow, and more advanced topics like GANs could benefit from deeper dives. Despite this, the course is recognized for its up-to-date content and ability to prepare students for real-world deep learning tasks.

The course uses the latest TensorFlow 2 framework and Keras API.

"Everything is up-to-date with TF2."

"Excellent course for getting started with TensorFlow 2 and Keras."

"I learned how to use the latest updates to TensorFlow and leverage the Keras API."

Provides a strong base, including Python data science prerequisites.

"The course provides a solid foundation, starting from NumPy and Pandas, which was a great refresher."

"I came to this course with only basic Python and it built up my skills impressively."

"This course is truly a bootcamp, preparing you for real-world deep learning tasks."

Strong emphasis on hands-on coding and practical, real-world projects.

"The hands-on projects are super helpful and solidify the learning."

"The practical exercises are well-designed, and I feel confident building my own models now."

"The balance between theory and practice is perfect. The Jupyter notebooks are a huge plus..."

"I came to this course with only basic Python and it built up my skills impressively. The hands-on coding was key."

Instructor excels at simplifying complex deep learning concepts.

"The instructor explains complex concepts with such clarity and makes them easy to grasp."

"Overall a very good course. The instructor is knowledgeable and presents material clearly."

"One of the best deep learning courses I’ve taken. The instructor’s teaching style is engaging..."

"I appreciate the clear explanations of complex concepts and the practical code examples."

Some reviewers found code examples occasionally unclear or requiring debugging.

"I found some of the code examples to be a bit messy and not always explained clearly line by line."

"I had to spend extra time debugging or figuring out why certain choices were made."

Pacing can be slow for advanced users; some advanced topics lack depth.

"If you already know NumPy, Pandas, etc., the initial sections feel very slow and basic."

"I found some parts, especially GANs, a bit rushed and could use more depth."

"It's a great start, but not an end-all for advanced topics."

"It sets you up, but you'll need external resources to truly master these topics."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Complete Tensorflow 2 and Keras Deep Learning Bootcamp with these activities:

Review Python Basics

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This course assumes a basic understanding of Python. This activity will help you refresh your knowledge and ensure you're ready to tackle the course materials.

Browse courses on Python Programming

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Review Online Tutorials or Documentation
Solve Coding Challenges and Practice Exercises

Read 'Deep Learning with Python'

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This book provides a comprehensive overview of deep learning concepts and techniques, including TensorFlow, Keras, and other essential tools.

View Deep Learning with Python, Second Edition on Amazon

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Read Chapters 1-4
Review and Summarize Key Concepts

Join a study group or discussion forum for TensorFlow

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Collaborate with peers to discuss TensorFlow concepts, share knowledge, and work on projects together.

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Find a study group or discussion forum dedicated to TensorFlow.
Participate in discussions and ask questions.
Collaborate on projects and learn from others.

11 other activities

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Attend a TensorFlow Workshop

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Workshops provide an excellent opportunity to learn from experts, ask questions, and gain hands-on experience with TensorFlow.

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Research and Identify Relevant Workshops
Register and Attend the Workshop
Participate Actively and Network

Practice creating and training neural networks with TensorFlow and Keras

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Reinforce your understanding of TensorFlow and Keras by practicing creating and training neural networks on various datasets.

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Choose a dataset and define the model architecture.
Preprocess the data and prepare it for training.
Train the model and evaluate its performance.

Discuss and Collaborate on Projects

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Working with peers can provide valuable insights and perspectives. This activity will help you connect and collaborate with other learners, exchange ideas, and refine your project ideas.

Browse courses on Collaborative Learning

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Find a Study Partner or Group
Set Regular Meeting Times
Discuss Project Ideas and Approaches

Follow tutorials on advanced TensorFlow techniques

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Explore advanced TensorFlow techniques by following tutorials on topics such as distributed training, model optimization, or generative adversarial networks.

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Identify an advanced TensorFlow technique you want to learn.
Find a high-quality tutorial on the topic.
Follow the tutorial and implement the technique.

Simulate and Test Keras Models

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Keras provides a range of features, such as early stopping, model checkpoints, and optimizers, that will help you evaluate and improve your models.

Browse courses on Keras

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Define Metrics and Loss Functions
Build and Train a Model
Evaluate and Modify Your Model

Write a blog post or article about your experiences with TensorFlow

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Reflect on your learning journey with TensorFlow by writing a blog post or article that shares your experiences and insights.

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Choose a topic related to TensorFlow that you're passionate about.
Write a well-structured and informative blog post.
Share your blog post with the community.

Create CNN Image Classification Models

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Deep learning models can be difficult to debug, especially when working with images. This activity will help you gain experience in troubleshooting and debugging your CNN models.

Browse courses on Convolutional Neural Networks

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Load and Preprocess Image Data
Build and Train a CNN Model
Evaluate and Debug Your Model

Participate in a TensorFlow hackathon or competition

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Challenge yourself and showcase your TensorFlow skills by participating in a hackathon or competition.

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Find a TensorFlow-related hackathon or competition.
Form a team and brainstorm ideas.
Develop and submit your solution.

Explore TensorFlow Model Optimizations

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TensorFlow provides a range of techniques to optimize your models for deployment. This activity will help you understand and apply these techniques to improve the efficiency of your models.

Browse courses on Machine Learning Deployment

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Identify Optimization Opportunities
Quantization and Pruning
Model Conversion and Deployment

Contribute to Open Source Projects

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Contributing to open source projects not only benefits the community but also provides you with valuable experience and insights into real-world applications of TensorFlow.

Browse courses on Software Development

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Identify Open Source Projects
Review Code and Find Issues to Contribute
Submit Pull Requests

Create a Machine Learning Project Portfolio

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A portfolio of projects will provide tangible evidence of your skills and knowledge to potential employers or clients.

Browse courses on Portfolio Development

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Identify and Select Projects
Document and Describe Your Projects
Create a Showcase Website or Repository

Career center

Learners who complete Complete Tensorflow 2 and Keras Deep Learning Bootcamp will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

As a Machine Learning Engineer, you will design, build, test, and deploy machine learning models. You will use a variety of tools and techniques to do this, including TensorFlow and Keras. This course will help you build the skills you need to succeed in this role. You will learn the basics of TensorFlow and Keras, as well as how to use them to build and train machine learning models. You will also learn about the different types of machine learning models and how to choose the right model for your project.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

As a Data Scientist, you will use data to solve business problems. You will use a variety of tools and techniques to do this, including TensorFlow and Keras. This course will help you build the skills you need to succeed in this role. You will learn the basics of TensorFlow and Keras, as well as how to use them to build and train machine learning models. You will also learn about the different types of machine learning models and how to choose the right model for your project.

See salaries and explore the career path for Data Scientist

Software Engineer

As a Software Engineer, you will design, build, and test software applications. You will use a variety of tools and techniques to do this, including TensorFlow and Keras. This course will help you build the skills you need to succeed in this role. You will learn the basics of TensorFlow and Keras, as well as how to use them to build and train machine learning models. You will also learn about the different types of machine learning models and how to choose the right model for your project.

See salaries and explore the career path for Software Engineer

Deep Learning Engineer

As a Deep Learning Engineer, you will design, build, and test deep learning models. You will use a variety of tools and techniques to do this, including TensorFlow and Keras. This course will help you build the skills you need to succeed in this role. You will learn the basics of TensorFlow and Keras, as well as how to use them to build and train deep learning models. You will also learn about the different types of deep learning models and how to choose the right model for your project.

See salaries and explore the career path for Deep Learning Engineer

AI Engineer

As an AI Engineer, you will design, build, and test AI systems. You will use a variety of tools and techniques to do this, including TensorFlow and Keras. This course will help you build the skills you need to succeed in this role. You will learn the basics of TensorFlow and Keras, as well as how to use them to build and train AI models. You will also learn about the different types of AI models and how to choose the right model for your project.

See salaries and explore the career path for AI Engineer

Computer Vision Engineer

As a Computer Vision Engineer, you will design, build, and test computer vision systems. You will use a variety of tools and techniques to do this, including TensorFlow and Keras. This course will help you build the skills you need to succeed in this role. You will learn the basics of TensorFlow and Keras, as well as how to use them to build and train computer vision models. You will also learn about the different types of computer vision models and how to choose the right model for your project.

See salaries and explore the career path for Computer Vision Engineer

Natural Language Processing Engineer

As a Natural Language Processing Engineer, you will design, build, and test natural language processing systems. You will use a variety of tools and techniques to do this, including TensorFlow and Keras. This course will help you build the skills you need to succeed in this role. You will learn the basics of TensorFlow and Keras, as well as how to use them to build and train natural language processing models. You will also learn about the different types of natural language processing models and how to choose the right model for your project.

See salaries and explore the career path for Natural Language Processing Engineer

Machine Learning Researcher

As a Machine Learning Researcher, you will conduct research on new machine learning algorithms and techniques. You will use a variety of tools and techniques to do this, including TensorFlow and Keras. This course will help you build the skills you need to succeed in this role. You will learn the basics of TensorFlow and Keras, as well as how to use them to build and train machine learning models. You will also learn about the different types of machine learning models and how to choose the right model for your project.

See salaries and explore the career path for Machine Learning Researcher

Data Analyst

As a Data Analyst, you will use data to solve business problems. You will use a variety of tools and techniques to do this, including TensorFlow and Keras. This course will help you build the skills you need to succeed in this role. You will learn the basics of TensorFlow and Keras, as well as how to use them to build and train machine learning models. You will also learn about the different types of machine learning models and how to choose the right model for your project.

See salaries and explore the career path for Data Analyst

Business Analyst

As a Business Analyst, you will use data to solve business problems. You will use a variety of tools and techniques to do this, including TensorFlow and Keras. This course will help you build the skills you need to succeed in this role. You will learn the basics of TensorFlow and Keras, as well as how to use them to build and train machine learning models. You will also learn about the different types of machine learning models and how to choose the right model for your project.

See salaries and explore the career path for Business Analyst

Product Manager

As a Product Manager, you will work with engineers and designers to build products that meet the needs of users. You will use data to make decisions about what products to build, how to design them, and how to market them. This course will help you build the skills you need to succeed in this role. You will learn the basics of TensorFlow and Keras, as well as how to use them to build and train machine learning models. You will also learn about the different types of machine learning models and how to choose the right model for your project.

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Quantitative Analyst

As a Quantitative Analyst, you will use data to make investment decisions. You will use a variety of tools and techniques to do this, including TensorFlow and Keras. This course will help you build the skills you need to succeed in this role. You will learn the basics of TensorFlow and Keras, as well as how to use them to build and train machine learning models. You will also learn about the different types of machine learning models and how to choose the right model for your project.

See salaries and explore the career path for Quantitative Analyst

Statistician

As a Statistician, you will use data to solve problems. You will use a variety of tools and techniques to do this, including TensorFlow and Keras. This course will help you build the skills you need to succeed in this role. You will learn the basics of TensorFlow and Keras, as well as how to use them to build and train machine learning models. You will also learn about the different types of machine learning models and how to choose the right model for your project.

See salaries and explore the career path for Statistician

Software Developer

As a Software Developer, you will design, build, and test software applications. You will use a variety of tools and techniques to do this, including TensorFlow and Keras. This course will help you build the skills you need to succeed in this role. You will learn the basics of TensorFlow and Keras, as well as how to use them to build and train machine learning models. You will also learn about the different types of machine learning models and how to choose the right model for your project.

See salaries and explore the career path for Software Developer

Data Engineer

As a Data Engineer, you will build and maintain data pipelines. You will use a variety of tools and techniques to do this, including TensorFlow and Keras. This course will help you build the skills you need to succeed in this role. You will learn the basics of TensorFlow and Keras, as well as how to use them to build and train machine learning models. You will also learn about the different types of machine learning models and how to choose the right model for your project.

See salaries and explore the career path for Data Engineer