Hands-On One-shot Learning with Python : Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch

Hands-On One-shot Learning with Python : Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch

Enregistré dans:

Détails bibliographiques
Auteur principal:	Jadon, Shruti. (Auteur)
Autres auteurs:	Garg, Ankush. (Auteur)
Support:	E-Book
Langue:	Anglais
Publié:	Birmingham : Packt Publishing, 2020.
Autres localisations:	Voir dans le Sudoc
Accès en ligne:	Accès à l'E-book

Documents similaires

Hands-on meta learning with Python : meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow
par: Ravichandiran, Sudharsan.
Publié: (2018)

Hands-on unsupervised learning with Python : implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more
par: Bonaccorso, Giuseppe.
Publié: (2019)

Python deep learning : exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow
Publié: (2019)

Machine Learning with PyTorch and Scikit-Learn : Develop machine learning and deep learning models with Python
par: Raschka, Sebastian.
Publié: (2022)

Deep learning with PyTorch : a practical approach to building neural network models using PyTorch
par: Subramanian, Vishnu (19..-....).
Publié: (2018)

Hands-on transfer learning with Python : implement advanced deep learning and neural network models using TensorFlow and Keras
par: Sarkar, Dipanjan (19..-....).
Publié: (2018)

Deep learning with PyTorch quick start guide : learn to train and deploy neural network models in Python
par: Julian, David.
Publié: (2018)

Practical Deep Reinforcement Learning with Python : Concise Implementation of Algorithms, Simplified Maths, and Effective Use of TensorFlow and PyTorch
par: Gridin, Ivan.

PyTorch Deep Learning Hands-On : Apply modern AI techniques with CNNs, RNNs, GANs, reinforcement learning, and more
par: Thomas, Sherin.
Publié: (2019)

Hands-On Graph Neural Networks Using Python : Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch
par: Labonne, Maxime.

Advanced Deep Learning with Python : Design and implement advanced next-generation AI solutionsusing TensorFlow and PyTorch
par: Vasilev, Ivan.
Publié: (2019)

Hands-On Deep Learning Algorithms with Python : Master deep learning algorithms with extensive math by implementing them using TensorFlow
par: Ravichandiran, Sudharsan.
Publié: (2019)

Python Machine Learning By Example : Build intelligent systems using Python, TensorFlow 2, PyTorch, and scikit-learn
par: Liu, Yuxi (Hayden).
Publié: (2020)

The deep learning with PyTorch workshop : build deep neural networks and artificial intelligence applications with PyTorch
par: Saleh, Hyatt.
Publié: (2020)

Hands-on Supervised Learning with Python : Learn How to Solve Machine Learning Problems with Supervised Learning Algorithms Using Python
par: Shang, Madeleine.

3D Deep Learning with Python : Design and develop your computer vision model with 3D data using PyTorch3D and more
par: Ma, Xudong.
Publié: (2022)

Hands-on reinforcement learning with Python : master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow
par: Ravichandiran, Sudharsan.
Publié: (2018)

Hands-On Ensemble Learning with Python : Build highly optimized ensemble machine learning models using scikit-learn and Keras
par: Kyriakides, George.
Publié: (2019)

Deep Learning for Time Series Cookbook : Use PyTorch and Python recipes for forecasting, classification, and anomaly detection
par: Cerqueira, Vitor.

Deep Learning with PyTorch Lightning : Swiftly build high-performance Articial Intelligence (AI) models using Python
par: Sawarkar, Kunal.
Publié: (2022)

Production-Ready Applied Deep Learning : Learn how to construct and deploy complex models in PyTorch and TensorFlow deep learning frameworks
par: Palczewski, Tomasz.
Publié: (2022)

Hands-On Deep Learning Architectures with Python : Create deep neural networks to solve computational problems using TensorFlow and Keras
par: Liu, Yuxi (Hayden).
Publié: (2019)

Hands-on Markov models with Python : implement probabilistic models for learning complex data sequences using the Python ecosystem
par: Ankan, Ankur.
Publié: (2018)

Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits : A practical guide to implementing supervised and unsupervised machine learning algorithms in Python
par: Amr, Tarek (19..-....).
Publié: (2020)

Hands-on data science and Python machine learning : perform data mining and machine learning efficiently using Python and Spark
par: Kane, Frank.
Publié: (2017)

Hands-On Natural Language Processing with PyTorch 1.x : Build smart, AI-driven linguistic applications using deep learning and NLP techniques
par: Dop, Thomas.
Publié: (2020)

Hands-On Q-Learning with Python : Practical Q-learning with OpenAI Gym, Keras, and TensorFlow
par: Habib, Nazia.
Publié: (2019)

Hands-On Deep Learning with Go : A practical guide to building and implementing neural network models using Go
par: Seneque, Gareth.
Publié: (2019)

PyTorch 1.x reinforcement learning cookbook : over 60 recipes to design, develop, and deploy self-learning AI models using Python
par: Liu, Yuxi (Hayden).
Publié: (2019)

Time Series Forecasting using Deep Learning : Combining PyTorch, RNN, TCN, and Deep Neural Network Models to Provide Production-Ready Prediction Solutions
par: Gridin, Ivan.

Python Machine Learning : Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2
par: Raschka, Sebastian.
Publié: (2019)

Artificial Intelligence with Python Cookbook : Proven recipes for applying AI algorithms and deep learning techniques using TensorFlow 2.x and PyTorch 1.6
par: Auffarth, Ben.
Publié: (2020)

Learn SQL using MySQL in One Day and Learn It Well : SQL for beginners with Hands-on Project
par: Chan, Jamie.

Hands-On Machine Learning with IBM Watson : Leverage IBM Watson to Implement Machine Learning Techniques and Algorithms Using Python
par: Miller, James D..
Publié: (2019)

Hands-On Generative Adversarial Networks with PyTorch 1.x : Implement next-generation neural networks to build powerful GAN models using Python
par: Hany, John.
Publié: (2019)

Hands-On Mathematics for Deep Learning : Build a solid mathematical foundation for training eﬃcient deep neural networks
par: Dawani, Jay.
Publié: (2020)

Python deep learning cookbook
par: Bakker, Indra Den.
Publié: (2017)

Machine Learning with Python : Design and Develop Machine Learning and Deep Learning Technique using real world code examples
par: Vijayvargia, Abhishek.

Hands-on deep learning with TensorFlow
par: Boxel, Dan Van.
Publié: (2017)

Accelerate Model Training with PyTorch 2.X : Build more accurate models by boosting the model training process
par: Alves, Maicon Melo.

Université catholique de l'Ouest - Bibliothèques - 3 place André Leroy - BP10808 - 49008 ANGERS Cedex 1