Cover Image

QR Code

Deep learning illustrated : a visual, interactive guide to artificial intelligence

Main Author:	Krohn, Jon
Subjects:	Machine learning Artificial intelligence Electronic books
Online Access:	http://library.unisel.edu.my/web/guest/mylibrary

Similar Items

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

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

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

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

Transfer learning

Robust machine learning : distributed methods for safe AI
by: Guerraoui, Rachid

Practical machine learning in Javascript : tensorflow.js for web developers
by: Gerard, Charley

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

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

Deep reinforcement learning
by: Plaat, Aske

Empowering artificial intelligence through machine learning : new advances and applications

Deep learning : a visual approach
by: Glassner, Andrew S.

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

Practicing trustworthy machine learning : consistent, transparent, and fair AI pipelines
by: Pruksachatkun, Yada

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

Generative adversarial networks for image-to-image translation

Machine learning for business : using Amazon SageMaker and Jupyter
by: Hudgeon, Doug

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

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

Machine intelligence and signal analysis
Published: (2019)

Deep learning

Machine learning : a comprehensive beginner's guide
by: R., Akshay B.

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

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

Generative adversarial networks and deep learning : theory and applications

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

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

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

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

Machine learning with Dynamics 365 and Power Platform : the ultimate guide to apply predictive analytics
by: Clere, Aurelien

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

Hands-on deep learning with R : a practical guide to designing, building, and improving neural network models using R
by: Pawlus, Michael