Mastering Keras

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Explore powerful deep learning techniques using Keras.Successful data scientists need to be able to work with the most powerful tools to solve the most challenging problems. As deep learning becomes ever more entrenched as the gold-standard tool for a wide variety of advanced data analytics and Artificial Intelligence problems, it is essential for you as a data scientist or analyst to be comfortable wielding these powerful techniques on an ever-expanding array of problems.TensorFlow (and its easy-to-learn deep learning wrapper Keras) have become game-changers in permitting simple implementations of the most complex of deep learning techniques.In this course, we teach you to go beyond your working knowledge of Keras, begin to wield its full power, and unleash the amazing potential of advanced deep learning on your data science problems. You'll learn to design and train deep learning models for synthetic data generation, object detection, one-shot learning, and much more.By the end of this course, you will be able to implement many advanced deep learning modelling algorithms and adapt them to your own purposes. Perhaps the next great breakthrough will come from you?Please note that familiarity with machine learning and deep learning approaches, together with practical experience with Keras and Python programming, are assumed for taking this course.All related code files are placed on a GitHub repository at: About the Author
.
Mike Ashcroft, PhD, is a lecturer at Uppsala University in Sweden. He teaches Masters and PhD students Artificial Intelligence and Statistical Machine Learning. He has created and delivered courses for the European Data Science Academy, Future Learn/Open University, and Sichuan University. He has a deep knowledge of, and experience working with, Keras

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Online

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Different dates availableEnrolment now open

About this course

Use the powerfully functional Keras API to design and implement advanced deep learning techniques
Design and implement advanced Convolutional Neural Networks for powerful image classification
Design and implement object detection networks to identify objects present in images and their location
Work with deep generative neural networks for synthetic data generation and semi-supervised learning
Develop a stable deep reinforcement-learning system and learn to make optimal decisions via feedback from their environment
Implement deep one-shot learning systems that can classify new instances of a class after a single exposure to such an object

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This centre's achievements

2021

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The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 4 years

Subjects

  • Network Training
  • University
  • Image
  • Design
  • Teaching
  • Data analysis
  • Network
  • Artificial Intelligence

Course programme

Preparing Yourself for Mastering Keras Journey 3 lectures 14:30 The Course Overview This video gives an overview of the entire course. Keras and TensorFlow Functionality Get a basic overview of what Keras and TensorFlow are, and the relationship between them.
  • Explain Keras
  • Explain TensorFlow
Setting Up the Environment and Teaching Methodology Get a basic overview of tools used and discuss the teaching methodology being followed.
  • Explain Colab
  • Look at teaching methodology
Preparing Yourself for Mastering Keras Journey - Quiz Preparing Yourself for Mastering Keras Journey 3 lectures 14:30 The Course Overview This video gives an overview of the entire course. Keras and TensorFlow Functionality Get a basic overview of what Keras and TensorFlow are, and the relationship between them.
  • Explain Keras
  • Explain TensorFlow
Setting Up the Environment and Teaching Methodology Get a basic overview of tools used and discuss the teaching methodology being followed.
  • Explain Colab
  • Look at teaching methodology
Preparing Yourself for Mastering Keras Journey - Quiz The Course Overview This video gives an overview of the entire course. The Course Overview This video gives an overview of the entire course. The Course Overview This video gives an overview of the entire course. The Course Overview This video gives an overview of the entire course. This video gives an overview of the entire course. This video gives an overview of the entire course. Keras and TensorFlow Functionality Get a basic overview of what Keras and TensorFlow are, and the relationship between them.
  • Explain Keras
  • Explain TensorFlow
Keras and TensorFlow Functionality Get a basic overview of what Keras and TensorFlow are, and the relationship between them.
  • Explain Keras
  • Explain TensorFlow
Keras and TensorFlow Functionality Get a basic overview of what Keras and TensorFlow are, and the relationship between them.
  • Explain Keras
  • Explain TensorFlow
Keras and TensorFlow Functionality Get a basic overview of what Keras and TensorFlow are, and the relationship between them.
  • Explain Keras
  • Explain TensorFlow
Get a basic overview of what Keras and TensorFlow are, and the relationship between them.
  • Explain Keras
  • Explain TensorFlow
Get a basic overview of what Keras and TensorFlow are, and the relationship between them.
  • Explain Keras
  • Explain TensorFlow
Setting Up the Environment and Teaching Methodology Get a basic overview of tools used and discuss the teaching methodology being followed.
  • Explain Colab
  • Look at teaching methodology
Setting Up the Environment and Teaching Methodology Get a basic overview of tools used and discuss the teaching methodology being followed.
  • Explain Colab
  • Look at teaching methodology
Setting Up the Environment and Teaching Methodology Get a basic overview of tools used and discuss the teaching methodology being followed.
  • Explain Colab
  • Look at teaching methodology
Setting Up the Environment and Teaching Methodology Get a basic overview of tools used and discuss the teaching methodology being followed.
  • Explain Colab
  • Look at teaching methodology
Get a basic overview of tools used and discuss the teaching methodology being followed.
  • Explain Colab
  • Look at teaching methodology
Get a basic overview of tools used and discuss the teaching methodology being followed.
  • Explain Colab
  • Look at teaching methodology
Preparing Yourself for Mastering Keras Journey - Quiz Preparing Yourself for Mastering Keras Journey - Quiz Preparing Yourself for Mastering Keras Journey - Quiz Preparing Yourself for Mastering Keras Journey - Quiz Working with the Keras Functional API 4 lectures 48:16 MLPs and Simple Data Analytics In this video, we’ll do a review of working with MLPs.
  • Design MLPs using the Keras functional API
  • Implement regularization and batch normalization layers
  • Work with validation data and early stopping
CNNs and Basic Image Classification Here, we implement a CNN for image classification in the Keras functional API.
  • Design basic CNNs using the Keras functional API
  • Implement dropout regularization
RNNs and Sequential Data Analysis In this video, we’ll have look at implementing a LSTM in the Keras functional API.
  • Design LSTMs using the Keras functional API
  • Mount a Google drive to Colab for file i/o
  • Generate synthetic data from a LSTM and sequence seed
AEs and Denoising Data Here, we implement a denoising auto-encoder in the Keras functional API.
  • Design denoising AEs using the Keras functional API
  • Understand denoising auto-encoders
Working with the Keras Functional API - Quiz What is the difference between the two keras functions used to create a network: Model and Sequential? Working with the Keras Functional API 4 lectures 48:16 MLPs and Simple Data Analytics In this video, we’ll do a review of working with MLPs.
  • Design MLPs using the Keras functional API
  • Implement regularization and batch normalization layers
  • Work with validation data and early stopping
CNNs and Basic Image Classification Here, we implement a CNN for image classification in the Keras functional API.
  • Design basic CNNs using the Keras functional API
  • Implement dropout regularization
RNNs and Sequential Data Analysis In this video, we’ll have look at implementing a LSTM in the Keras functional API.
  • Design LSTMs using the Keras functional API
  • Mount a Google drive to Colab for file i/o
  • Generate synthetic data from a LSTM and sequence seed
AEs and Denoising Data Here, we implement a denoising auto-encoder in the Keras functional API.
  • Design denoising AEs using the Keras functional API
  • Understand denoising auto-encoders
Working with the Keras Functional API - Quiz What is the difference between the two keras functions used to create a network: Model and Sequential? MLPs and Simple Data Analytics In this video, we’ll do a review of working with MLPs.
  • Design MLPs using the Keras functional API
  • Implement regularization and batch normalization layers
  • Work with validation data and early stopping
MLPs and Simple Data Analytics In this video, we’ll do a review of working with MLPs.
  • Design MLPs using the Keras functional API
  • Implement regularization and batch normalization layers
  • Work with validation data and early stopping
MLPs and Simple Data Analytics In this video, we’ll do a review of working with MLPs.
  • Design MLPs using the Keras functional API
  • Implement regularization and batch normalization layers
  • Work with validation data and early stopping
MLPs and Simple Data Analytics In this video, we’ll do a review of working with MLPs.
  • Design MLPs using the Keras functional API
  • Implement regularization and batch normalization layers
  • Work with validation data and early stopping
In this video, we’ll do a review of working with MLPs.
  • Design MLPs using the Keras functional API
  • Implement regularization and batch normalization layers
  • Work with validation data and early stopping
In this video, we’ll do a review of working with MLPs.
  • Design MLPs using the Keras functional API
  • Implement regularization and batch normalization layers
  • Work with validation data and early stopping
CNNs and Basic Image Classification Here, we implement a CNN for image classification in the Keras functional API.
  • Design basic CNNs using the Keras functional API
  • Implement dropout regularization
CNNs and Basic Image Classification Here, we implement a CNN for image classification in the Keras functional API.
  • Design basic CNNs using the Keras functional API
  • Implement dropout regularization
CNNs and Basic Image Classification Here, we implement a CNN for image classification in the Keras functional API.
  • Design basic CNNs using the Keras functional API
  • Implement dropout regularization
CNNs and Basic Image Classification Here, we implement a CNN for image classification in the Keras functional API.
  • Design basic CNNs using the Keras functional API
  • Implement dropout regularization
Here, we implement a CNN for image classification in the Keras functional API.
  • Design basic CNNs using the Keras functional API
  • Implement dropout regularization
Here, we implement a CNN for image classification in the Keras functional API.
  • Design basic CNNs using the Keras functional API
  • Implement dropout regularization
RNNs and Sequential Data Analysis In this video, we’ll have look at implementing a LSTM in the Keras functional API.
  • Design LSTMs using the Keras functional API
  • Mount a Google drive to Colab for file i/o
  • Generate synthetic data from a LSTM and sequence seed
RNNs and Sequential Data Analysis In this video, we’ll have look at implementing a LSTM in the Keras functional API.
  • Design LSTMs using the Keras functional API
  • Mount a Google drive to Colab for file i/o
  • Generate synthetic data from a LSTM and sequence seed
RNNs and Sequential Data Analysis In this video, we’ll have look at implementing a LSTM in the Keras functional API.
  • Design LSTMs using the Keras functional API
  • Mount a Google drive to Colab for file i/o
  • Generate synthetic data from a LSTM and sequence seed
RNNs and Sequential Data Analysis In this video, we’ll have look at implementing a LSTM in the Keras functional API.
  • Design LSTMs using the Keras functional API
  • Mount a Google drive to Colab for file i/o
  • Generate synthetic data from a LSTM and sequence seed
In this video, we’ll have look at implementing a LSTM in the Keras functional API.
  • Design LSTMs using the Keras functional API
  • Mount a Google drive to Colab for file i/o
  • Generate synthetic data from a LSTM and sequence seed
In this video, we’ll have look at implementing a LSTM in the Keras functional API.
  • Design LSTMs using the Keras functional API
  • Mount a Google drive to Colab for file i/o
  • Generate synthetic data from a LSTM and sequence seed
AEs and Denoising Data Here, we implement a denoising auto-encoder in the Keras functional API.
  • Design denoising AEs using the Keras functional API
  • Understand denoising auto-encoders
AEs and Denoising Data Here, we implement a denoising auto-encoder in the Keras functional API.
  • Design denoising AEs using the Keras functional API
  • Understand denoising auto-encoders
AEs and Denoising Data Here, we implement a denoising auto-encoder in the Keras functional API.
  • Design denoising AEs using the Keras functional API
  • Understand denoising auto-encoders
AEs and Denoising Data Here, we implement a denoising auto-encoder in the Keras functional API.
  • Design denoising AEs using the Keras functional API
  • Understand denoising auto-encoders
Here, we implement a denoising auto-encoder in the Keras functional API.
  • Design denoising AEs using the Keras functional API
  • Understand denoising auto-encoders
Here, we implement a denoising auto-encoder in the Keras functional API.
  • Design denoising AEs using the Keras functional API
  • Understand denoising auto-encoders
Working with the Keras Functional API - Quiz What is the difference between the two keras functions used to create a network: Model and Sequential? Working with the Keras Functional API - Quiz What is the difference between the two keras functions used to create a network: Model and Sequential? Working with the Keras Functional API - Quiz What is the difference between the two keras functions used to create a network: Model and Sequential? Working with the Keras Functional API - Quiz What is the difference between the two keras functions used to create a network: Model and Sequential? What is the difference between the two keras functions used to create a network: Model and Sequential? What is the difference between the two keras functions used to create a network: Model and Sequential? Developing and Implementing Deep Generative Models. 3 lectures 41:36 What Can Generative Models Do for Me? We discuss generative models and synthetic data, focusing on when and in what ways synthetic data is useful Dense Networks We’ll look at the ideas behind dense layers and networks, code its blocks. Create basic models and visually examine the dense architecture.
  • Look at the ideas...

Additional information

Familiarity with machine learning approaches and practical experience with Keras are assumed. Fluency with Python programming is assumed

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Mastering Keras

£ 150 + VAT

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