Sumbangan 15 September 2024 – 1 Oktober 2024 Tentang pengumpulan dana

Practical Convolutional Neural Networks: Implement advanced...

Main
Computers - Computer Science
Practical Convolutional Neural...

Practical Convolutional Neural Networks: Implement advanced deep learning models using Python

Mohit Sewak, Rezaul Karim, Pradeep Pujari

5.0 / 5.0

Sukakah Anda buku ini?

Bagaimana kualitas file yang diunduh?

Unduh buku untuk menilai kualitasnya

Bagaimana kualitas file yang diunduh?

Kategori:

Computers - Computer Science

Tahun:

2018

Penerbit:

Packt Publishing

Bahasa:

english

ISBN 10:

1788392302

ISBN 13:

9781788392303

File:

PDF, 16.31 MB

IPFS:

,

english, 2018

Membaca daring

Pengubahan menjadi sedang diproses

Pengubahan menjadi gagal

Mungkin Anda tertarik

The LazyProgrammer — Convolutional Neural Networks in Python: Master Data Science and Machine Learning with Modern Deep Learning in Python, Theano, and TensorFlow (Machine Learning in Python)

Md. Forhad Ali — Fruits Classification using Convolutional Neural Network

LazyProgrammer — Convolutional Neural Networks in Python: Master Data Science and Machine Learning with Modern Deep Learning in Python, Theano, and TensorFlow (Machine Learning in Python)

Suykens J. — A short Introduction to Support Vector Machines and Kernelbased Learning

Shangyu Sun, Huayi Wu, Longgang Xiang — City-Wide Traffic Flow Forecasting Using a Deep Convolutional Neural Network

Loris Nanni, Alessandra Lumini, Stefano Ghidoni, Gianluca Maguolo — Stochastic Selection of Activation Layers for Convolutional Neural Networks

Francesco Mosconi — Zero to Deep Learning with Keras and Tensorflow

Russell Reed, Robert J MarksII — Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks

Saban Ozturk — Convolutional Neural Networks for Medical Image Processing Applications

Ragav Venkatesan, Baoxin Li — Convolutional Neural Networks in Visual Computing: A Concise Guide

Larry Medsker, Lakhmi C. Jain — Recurrent Neural Networks: Design and Applications

Aurélien Géron — Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Seth Weidman — Deep Learning from Scratch: Building With Python From First Principles

Laurentiu Spilca; [Laurențiu Spilcă] — Troubleshooting Java: Read, debug, and optimize JVM applications (Final Release)

Bakker, Indra den — Python deep learning cookbook: over 75 practical recipes on neural network modeling, reinforcement learning, and transfer learning using Python

Farrukh Akhtar — Practical Reinforcement Learning: Develop self-evolving, intelligent agents with OpenAI Gym, Python and Java

Yusuke Sugomori, Bostjan Kaluza, Fabio M. Soares, Alan M. F. Souza — Deep Learning. Practical Neural Networks with Java

Subramanian, Vishnu — Deep learning with PyTorch: a practical approach to building neural network models using PyTorch

Chiranji Lal Chowdhary (editor), Mamoun Alazab (editor), Ankit Chaudhary (editor), Saqib Hakak (editor), G. Thippa Reddy (editor) — Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches: Fundamentals, Technologies and Applications

Mohd Naved, V. Ajantha Devi, Loveleen Gaur, Ahmed A. Elngar — IoT-enabled Convolutional Neural Networks: Techniques and Applications

Ashwin Pajankar — Python 3 Image Processing: Learn Image Processing with Python 3, NumPy, Matplotlib, and Scikit-image

Nikhil Singh, Paras Ahuja — Fundamentals of Deep Learning and Computer Vision: A Complete Guide to become an Expert in Deep Learning...

Xiaolin Hu, P. Balasubramaniam — Recurrent Neural Networks

Lili Mou, Zhi Jin — Tree-Based Convolutional Neural Networks: Principles and Applications

Lili Mou, Zhi Jin — Tree-based Convolutional Neural Networks

Dutta P., Barman A — Human emotion recognition from face images

Teik Toe Teoh — Convolutional Neural Networks for Medical Applications

Williams, Anthony — Big Data: 4 Manuscripts – Data Analytics for Beginners, Deep Learning with Keras, Analyzing Data with Power BI, Convolutional Neural Networks in Python

dmrobinson — R Deep Learning Cookbook: Solve complex neural net problems with TensorFlow, H2O and MXNet

deep learning for computer vision — deep learning for computer vision

Biswas, Snehan & Mukherjee, Amartya & Dey, Nilanjan — A Beginner’s Guide to Medical Application Development with Deep Convolutional Neural Networks

Vasudevan, Shriram K, Pulari, Sini Raj, Vasudevan, Subashri — Deep Learning: A Comprehensive Guide

S. Poonkuntran, Rajesh Kumar Dhanraj, Balamurugan Balusamy — Object Detection with Deep Learning Models: Principles and Applications

Amit Kumar Tyagi (editor) — Computational Analysis and Deep Learning for Medical Care: Principles, Methods, and Applications

Mahmoud Hassaballah (editor), Ali Ismail Awad (editor) — Deep Learning in Computer Vision: Principles and Applications

Vaibhav Verdhan — Computer Vision Using Deep Learning: Neural Network Architectures with Python and Keras

Nikhil Buduma — Fundamentals of Deep Learning

Bharath Ramsundar — Tensorflow for Deep Learning: From Linear Regression to Reinforcement Learning

P Varalakshmi & J Julanta Leela Rachel — Recognition Of Fish Categories Using Deep Learning Technique

Mohamed Elgendy — Deep Learning for Vision Systems

Arvind Kumar Tiwari — Deep Learning and Its Applications

E. Golden Julie (editor), Y. Harold Robinson (editor), S. M. Jaisakthi (editor) — Handbook of Deep Learning in Biomedical Engineering and Health Informatics

Istilah kunci