Hands On Transfer Learning with Python Book [PDF] Download

Download the fantastic book titled Hands On Transfer Learning with Python written by Dipanjan Sarkar, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Hands On Transfer Learning with Python", which was released on 31 August 2018. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of Hands On Transfer Learning with Python by Dipanjan Sarkar PDF

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 Description Transfer 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 for Hands-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.


Detail About Hands On Transfer Learning with Python PDF

  • Author : Dipanjan Sarkar
  • Publisher : Packt Publishing Ltd
  • Genre : Computers
  • Total Pages : 430 pages
  • ISBN : 1788839056
  • PDF File Size : 41,5 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Hands-On Transfer Learning with Python

Hands-On Transfer Learning with Python
  • Publisher : Packt Publishing Ltd
  • File Size : 42,9 Mb
  • Release Date : 31 August 2018
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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

Hands-On Image Processing with Python

Hands-On Image Processing with Python
  • Publisher : Packt Publishing Ltd
  • File Size : 23,6 Mb
  • Release Date : 30 November 2018
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Explore the mathematical computations and algorithms for image processing using popular Python tools and frameworks. Key FeaturesPractical coverage of every image processing task with popular Python librariesIncludes topics such as

Hands-On One-shot Learning with Python

Hands-On One-shot Learning with Python
  • Publisher : Packt Publishing Ltd
  • File Size : 49,8 Mb
  • Release Date : 10 April 2020
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Get to grips with building powerful deep learning models using PyTorch and scikit-learn Key FeaturesLearn how you can speed up the deep learning process with one-shot learningUse Python and PyTorch

Hands-On Meta Learning with Python

Hands-On Meta Learning with Python
  • Publisher : Packt Publishing Ltd
  • File Size : 50,7 Mb
  • Release Date : 31 December 2018
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Explore a diverse set of meta-learning algorithms and techniques to enable human-like cognition for your machine learning models using various Python frameworks Key FeaturesUnderstand the foundations of meta learning algorithmsExplore

Intelligent Projects Using Python

Intelligent Projects Using Python
  • Publisher : Packt Publishing Ltd
  • File Size : 31,9 Mb
  • Release Date : 31 January 2019
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Implement machine learning and deep learning methodologies to build smart, cognitive AI projects using Python Key FeaturesA go-to guide to help you master AI algorithms and concepts8 real-world projects tackling

Hands-On Q-Learning with Python

Hands-On Q-Learning with Python
  • Publisher : Packt Publishing Ltd
  • File Size : 28,9 Mb
  • Release Date : 19 April 2019
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Leverage the power of reward-based training for your deep learning models with Python Key FeaturesUnderstand Q-learning algorithms to train neural networks using Markov Decision Process (MDP)Study practical deep reinforcement

Deep Learning with Python

Deep Learning with Python
  • Publisher : Simon and Schuster
  • File Size : 30,8 Mb
  • Release Date : 30 November 2017
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Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François

Hands-On Neural Networks with Keras

Hands-On Neural Networks with Keras
  • Publisher : Packt Publishing Ltd
  • File Size : 49,5 Mb
  • Release Date : 30 March 2019
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Your one-stop guide to learning and implementing artificial neural networks with Keras effectively Key FeaturesDesign and create neural network architectures on different domains using KerasIntegrate neural network models in your