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Hands-On Transfer Learning with Python - Implement advanced deep learning and neural network models using TensorFlow and Keras
Dipanjan Sarkar; Raghav Bali; Tamoghna Ghosh
Packt Publishing Limited (2018)
Pehmeäkantinen kirja
61,20
Tuotetta lisätty
ostoskoriin kpl
Siirry koriin
Text Analytics with Python - A Practical Real-World Approach to Gaining Actionable Insights from your Data
Dipanjan Sarkar
APress (2016)
Pehmeäkantinen kirja
41,70
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ostoskoriin kpl
Siirry koriin
Practical Machine Learning with Python - A Problem-Solver's Guide to Building Real-World Intelligent Systems
Dipanjan Sarkar; Raghav Bali; Tushar Sharma
APress (2017)
Pehmeäkantinen kirja
73,70
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ostoskoriin kpl
Siirry koriin
Text Analytics with Python - A Practitioner's Guide to Natural Language Processing
Dipanjan Sarkar
APress (2019)
Pehmeäkantinen kirja
38,10
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ostoskoriin kpl
Siirry koriin
R Machine Learning By Example
Raghav Bali; Dipanjan Sarkar
Packt Publishing Limited (2016)
Pehmeäkantinen kirja
65,10
Tuotetta lisätty
ostoskoriin kpl
Siirry koriin
Learning Social Media Analytics with R
Raghav Bali; Dipanjan Sarkar; Tushar Sharma
Packt Publishing Limited (2017)
Pehmeäkantinen kirja
67,10
Tuotetta lisätty
ostoskoriin kpl
Siirry koriin
R: Unleash Machine Learning Techniques
Raghav Bali; Dipanjan Sarkar; Brett Lantz; Cory Lesmeister
Packt Publishing Limited (2016)
Pehmeäkantinen kirja
127,50
Tuotetta lisätty
ostoskoriin kpl
Siirry koriin
Hands-On Transfer Learning with Python - Implement advanced deep learning and neural network models using TensorFlow and Keras
61,20 €
Packt Publishing Limited
Sivumäärä: 438 sivua
Asu: Pehmeäkantinen kirja
Julkaisuvuosi: 2018, 31.08.2018 (lisätietoa)
Kieli: Englanti
Deep learning simplified by taking supervised, unsupervised, and reinforcement learning to the next level using the Python ecosystem

Key Features

Build deep learning models with transfer learning principles in Python
implement transfer learning to solve real-world research problems
Perform complex operations such as image captioning neural style transfer

Book DescriptionTransfer learning is a machine learning (ML) technique where knowledge gained during training a set of problems can be used to solve other similar problems.

The purpose of this book is two-fold; firstly, we focus on detailed coverage of deep learning (DL) and transfer learning, comparing and contrasting the two with easy-to-follow concepts and examples. The second area of focus is real-world examples and research problems using TensorFlow, Keras, and the Python ecosystem with hands-on examples.

The book starts with the key essential concepts of ML and DL, followed by depiction and coverage of important DL architectures such as convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), and capsule networks. Our focus then shifts to transfer learning concepts, such as model freezing, fine-tuning, pre-trained models including VGG, inception, ResNet, and how these systems perform better than DL models with practical examples. In the concluding chapters, we will focus on a multitude of real-world case studies and problems associated with areas such as computer vision, audio analysis and natural language processing (NLP).

By the end of this book, you will be able to implement both DL and transfer learning principles in your own systems.

What you will learn

Set up your own DL environment with graphics processing unit (GPU) and Cloud support
Delve into transfer learning principles with ML and DL models
Explore various DL architectures, including CNN, LSTM, and capsule networks
Learn about data and network representation and loss functions
Get to grips with models and strategies in transfer learning
Walk through potential challenges in building complex transfer learning models from scratch
Explore real-world research problems related to computer vision and audio analysis
Understand how transfer learning can be leveraged in NLP

Who this book is forHands-On Transfer Learning with Python is for data scientists, machine learning engineers, analysts and developers with an interest in data and applying state-of-the-art transfer learning methodologies to solve tough real-world problems. Basic proficiency in machine learning and Python is required.

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Tilaustuote | Arvioimme, että tuote lähetetään meiltä noin 4-5 viikossa | Tilaa jouluksi viimeistään 27.11.2024
Myymäläsaatavuus
Helsinki
Tapiola
Turku
Tampere
Hands-On Transfer Learning with Python - Implement advanced deep learning and neural network models using TensorFlow and Keraszoom
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ISBN:
9781788831307
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