Cover Image

QR Code

Deep learning : a visual approach

Main Author:	Glassner, Andrew S.
Subjects:	Neural networks (Computer science) Machine learning Electronic books
Online Access:	http://library.unisel.edu.my/web/guest/mylibrary

Similar Items

Generative adversarial networks and deep learning : theory and applications

A few things I know about her : a personally machine learning inspired approach to understand surrounding nature
by: Apolloni, Bruno

Introduction to deep learning : from logical calculus to artificial intelligence
by: Skansi, Sandro
Published: (2018)

Advanced deep learning with TensorFlow 2 and Keras : apply DL, GANs, VAEs, deep RL, unsupervised learning, object detection and segmentation, and more
by: Atienza, Rowel

Practical MATLAB deep learning : a project-based approach
by: Paluszek, Michael

Deep learning and scientific computing with R torch
by: Keydana, Sigrid

Hyperparameter tuning for machine and deep learning with : a practical guide

Pro deep learning with TensorFlow 2.0 : a mathematical approach to advanced artificial intelligence in Python
by: Pattanayak, Santanu

Deep learning pipeline : building a deep learning model with TensorFlow
by: El-Amir, Hisham

Swarm intelligence and evolutionary computation : theory, advances and applications in machine learning and deep learning
by: Kouziokas, Georgios N.

Neural networks and deep learning : a textbook
by: Aggarwal, Charu C
Published: (2018)

Deep learning : from big data to artificial intelligence with R
by: Tuffery, Stephane

The deep learning with Keras workshop : an interactive approach to understanding deep learning with Keras
by: Moocarme, Matthew

Deep learning

Machine learning for civil & environmental engineers : a practical approach to data-driven analysis, explainability, and causality
by: Naser, M. Z

Deep learning for data analytics : foundations, biomedical applications, and challenges

Learn TensorFlow 2.0 : implement machine learning and deep learning models with Python
by: Singh, Pramod

Trends in deep learning methodologies : algorithms, applications, and systems

Deep learning through sparse and low-rank modeling

Next-generation machine learning with Spark : covers XGBoost, LightGBM, Spark NLP, distributed deep learning with Keras, and more
by: Quinto, Butch

Deep learning and parallel computing environment for bioengineering systems
by: Sangiah, Arun Kumar

Advancement of deep learning and its applications in object detection and recognition

Foundations of machine learning
by: Mohri, Mehryar

Machine learning using TensorFlow cookbook : over 60 recipes on machine learning using deep learning solutions from Kaggle Masters and Google Developers Experts
by: Audevart, Alexia

Machine learning fundamentals : a concise introduction
by: Jiang, Hui

Industrial machine learning : using artificial intelligence as a transformational disruptor
by: Vermeulen, Andreas Francois

Advances in deep learning, artificial intelligence and robotics : proceedings of the 2nd International Conference on Deep Learning, Artificial Intelligence and Robotics, (ICDLAIR) 2020

Beginning deep learning with TensorFlow : work with Keras, MNIST data sets, and advanced neural networks
by: Long, Liangqu

Deep reinforcement learning
by: Plaat, Aske

Machine learning with the Raspberry Pi : experiments with data and computer vision
by: Norris, Donald J

Text mining with machine learning : principles and techniques
by: Zizka, Jan

Statistical modeling in machine learning : concepts and applications

Handbook of research on deep learning innovations and trends

Machine learning with R, the tidyverse, and mlr
by: Rhys, Hefin I

Practical machine learning with Rust : creating intelligent applications in Rust
by: Bhattacharjee, Joydeep

Hands-on machine learning with ML.NET : getting started with Microsoft ML.NET to implement popular machine learning algorithms in C#
by: Capellman, Jarred

Machine learning for decision sciences with case studies in Python
by: Sumathi, S

Machine learning for cyber security : 4th International Conference, ML4CS 2022, Guangzhou, China, December 2-4, 2022, proceedings : 4th International Conference, ML4CS 2022, Guangzhou, China, December 2-4, 2022, proceedings : part I

Machine learning theory and applications : hands-on use cases with Python on classical and quantum machines
by: Vasques, Xavier

Graph algorithms for data science : with examples in Neo4j
by: Bratanic, Tomaz