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- Python Deep Learning Projects. 9 projects demystifying neural network and deep learning models for building intelligent systems
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Python Deep Learning Projects. 9 projects demystifying neural network and deep learning models for building intelligent systems
Matthew Lamons, Rahul Kumar, Abhishek Nagaraja
Ebook
Deep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier.
Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You’ll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system.
Similarly, you’ll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you’ll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects.
By the end of this book, you will have gained knowledge to develop your own deep learning systems in a straightforward way and in an efficient way
Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You’ll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system.
Similarly, you’ll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you’ll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects.
By the end of this book, you will have gained knowledge to develop your own deep learning systems in a straightforward way and in an efficient way
- 1. Building Deep Learning Environment
- 2. Training Neural Network for Prediction using Regression
- 3. Word Vector representationusing Word2VEC (skip-gram) for word prediction
- 4. Build NLP pipeline for Open-Domain Question Answering
- 5. Sequence-to-sequence models for building chatbots
- 6. Generative Language modelling using Bi-LSTM for content creation
- 7. Building Speech Recognition with DeepSpeech2
- 8. Handwritten digits classification using ConvNets
- 9. Real-time Object Detection using OpenCV and TensorFlow
- 10. Building Face Recognition using OpenFace and Clustering
- 11. Automated Image Captioning with NeuralTalk model
- 12. Pose Estimation on 3D models using ConvNets
- 13. Image translation using GANs for style transfer
- 14. Develop anautonomous Agents with Deep Reinforcement Learning
- 15. Summary and Next Steps in Your Deep Learning Career
- Title: Python Deep Learning Projects. 9 projects demystifying neural network and deep learning models for building intelligent systems
- Author: Matthew Lamons, Rahul Kumar, Abhishek Nagaraja
- Original title: Python Deep Learning Projects. 9 projects demystifying neural network and deep learning models for building intelligent systems
- ISBN: 9781789134759, 9781789134759
- Date of issue: 2018-10-31
- Format: Ebook
- Item ID: e_15bu
- Publisher: Packt Publishing