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

Let's get an overview of the course and get you setup on your computer!

Auto-Welcome Message

Course Overview

Course Setup and Installation

FAQ - Frequently Asked Questions

PLEASE MAKE SURE TO WATCH THE COURSE OVERVIEW LECTURE.

PLEASE WATCH COURSE OVERVIEW LECTURE

Let's quickly get up to speed on some NumPy basics.

Introduction to NumPy

NumPy Arrays

Numpy Index Selection

NumPy Operations

NumPy Exercises

Numpy Exercises - Solutions

Let's learn the basics of Pandas and Data Analysis to use it later on in the course!

Introduction to Pandas

Pandas Series

Pandas DataFrames - Part One

Pandas DataFrames - Part Two

Pandas Missing Data

GroupBy Operations

Pandas Operations

Data Input and Output

Pandas Exercises

Pandas Exercises - Solutions

Let's learn the basics of some visualization techniques we will be using with Python.

Introduction to Python Visualization

Matplotlib Basics

Seaborn Basics

Data Visualization Exercises

Data Visualization Exercises - Solutions

Let's quickly go over some key ideas for general machine learning!

What is Machine Learning?

Supervised Learning Overview

Overfitting

Evaluating Performance - Classification Error Metrics

Evaluating Performance - Regression Error Metrics

Unsupervised Learning

Learn how to build basic Artificial Neural Networks for Classification and Regression Tasks

Introduction to ANN Section

Perceptron Model

Neural Networks

Activation Functions

Multi-Class Classification Considerations

Cost Functions and Gradient Descent

Backpropagation

TensorFlow vs. Keras Explained

Keras Syntax Basics - Part One - Preparing the Data

Keras Syntax Basics - Part Two - Creating and Training the Model

Keras Syntax Basics - Part Three - Model Evaluation

Keras Regression Code Along - Exploratory Data Analysis

Keras Regression Code Along - Exploratory Data Analysis - Continued

Keras Regression Code Along - Data Preprocessing and Creating a Model

Keras Regression Code Along - Model Evaluation and Predictions

Keras Classification Code Along - EDA and Preprocessing

Keras Classification - Dealing with Overfitting and Evaluation

TensorFlow 2.0 Keras Project Options Overview

TensorFlow 2.0 Keras Project Notebook Overview

Keras Project Solutions - Exploratory Data Analysis

Keras Project Solutions - Dealing with Missing Data

Keras Project Solutions - Dealing with Missing Data - Part Two

Keras Project Solutions - Categorical Data

Keras Project Solutions - Data PreProcessing

Keras Project Solutions - Creating and Training a Model

Keras Project Solutions - Model Evaluation

Tensorboard

Learn how to build Convolutional Neural Networks for Image Data with Deep Learning and Python

CNN Section Overview

Image Filters and Kernels

Convolutional Layers

Pooling Layers

MNIST Data Set Overview

CNN on MNIST - Part One - The Data

CNN on MNIST - Part Two - Creating and Training the Model

CNN on MNIST - Part Three - Model Evaluation

CNN on CIFAR-10 - Part One - The Data

CNN on CIFAR-10 - Part Two - Evaluating the Model

Downloading Data Set for Real Image Lectures

CNN on Real Image Files - Part One - Reading in the Data

CNN on Real Image Files - Part Two - Data Processing

CNN on Real Image Files - Part Three - Creating the Model

CNN on Real Image Files - Part Four - Evaluating the Model

CNN Exercise Overview

CNN Exercise Solutions

Learn how to work with sequence data with Recurrent Neural Networks

RNN Section Overview

RNN Basic Theory

Vanishing Gradients

LSTMS and GRU

RNN Batches

RNN on a Sine Wave - The Data

RNN on a Sine Wave - Batch Generator

RNN on a Sine Wave - Creating the Model

RNN on a Sine Wave - LSTMs and Forecasting

RNN on a Time Series - Part One

RNN on a Time Series - Part Two

RNN Exercise

RNN Exercise - Solutions

Bonus - Multivariate Time Series - RNN and LSTMs

Learn how to use Neural Networks for Natural Language Processing and Generating Text!

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

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

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

Expand to see all activities and additional details

Show all 14 activities

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:

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

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 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

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

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

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

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.

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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

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

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

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

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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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.

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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