Image Processing Tensorflow

Natural Language Processing with TensorFlow - Second Edition (Repost)  eBooks & eLearning

Posted by DZ123 at Nov. 12, 2024
Natural Language Processing with TensorFlow - Second Edition (Repost)

Thushan Ganegedara, "Natural Language Processing with TensorFlow - Second Edition: The definitive NLP book to implement the most sought-after machine learning models and tasks"
English | 2022 | ISBN: 1838641351 | PDF | pages: 515 | 17.4 mb

Complete Python Based Image Processing and Computer Vision  eBooks & eLearning

Posted by Sigha at Sept. 8, 2020
Complete Python Based Image Processing and Computer Vision

Complete Python Based Image Processing and Computer Vision
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 44100 Hz, 2ch | Size: 3.05 GB
Genre: eLearning Video | Duration: 60 lectures (5 hour, 24 mins) | Language: English

Computer Vision Python : Image Recognition & Manipulation : Deep Learning Computer Vision Python : Image Analysis Python

TensorFlow in Action  eBooks & eLearning

Posted by yoyoloit at Sept. 30, 2022
TensorFlow in Action

TensorFlow in Action
by Thushan Ganegedara

English | 2022 | ISBN: ‎ 1617298344 | 680 pages | True PDF | 39.24 MB

Mastering Computer Vision with TensorFlow 2.x: (Repost)  eBooks & eLearning

Posted by step778 at Sept. 22, 2022
Mastering Computer Vision with TensorFlow 2.x: (Repost)

Krishnendu Kar, "Mastering Computer Vision with TensorFlow 2.x: Build advanced computer vision applications using machine learning and deep learning techniques"
English | 2020 | pages: 419 | ISBN: 1838827064 | PDF | 57,1 mb

TensorFlow Deep Learning Projects (Repost)  eBooks & eLearning

Posted by DZ123 at May 20, 2022
TensorFlow Deep Learning Projects (Repost)

Luca Massaron, Alberto Boschetti, Alexey Grigorev, "TensorFlow Deep Learning Projects: 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning"
English | 2018 | ISBN: 1788398068 | EPUB | pages: 320 | 23.6 mb

Deep Learning Foundations: Natural Language Processing with TensorFlow  eBooks & eLearning

Posted by lucky_aut at April 19, 2021
Deep Learning Foundations: Natural Language Processing with TensorFlow

Deep Learning Foundations: Natural Language Processing with TensorFlow
Duration: 1h 47m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 285 MB
Genre: eLearning | Language: English
Hands-On Image Generation with TensorFlow: A practical guide to generating images and videos using deep learning [Repost]

Hands-On Image Generation with TensorFlow: A practical guide to generating images and videos using deep learning by Soon Yau Cheong
English | December 24, 2020 | ISBN: 1838826785 | True EPUB/PDF | 306 pages | 10.7/7.3 MB

Hands-On Computer Vision with TensorFlow 2 (Repost)  eBooks & eLearning

Posted by step778 at March 20, 2024
Hands-On Computer Vision with TensorFlow 2 (Repost)

Eliot Andres, "Hands-On Computer Vision with TensorFlow 2: Leverage deep learning to create powerful image processing apps with TensorFlow 2.0 and Keras"
English | 2019 | pages: 363 | ISBN: 1788830644 | PDF | 20,4 mb

Deep Learning with TensorFlow 2 and Keras - Second Edition (Code Files)  eBooks & eLearning

Posted by readerXXI at Dec. 24, 2020
Deep Learning with TensorFlow 2 and Keras - Second Edition (Code Files)

Deep Learning with TensorFlow 2 and Keras - Second Edition (Code Files)
By Antonio Gulli, Amita Kapoor
English | 2019 | ISBN: 1838823417 | - | Code Files (zip) | 47 MB

TensorFlow 2 Pocket Reference: Building and Deploying Machine Learning Models  eBooks & eLearning

Posted by First1 at July 29, 2021
TensorFlow 2 Pocket Reference: Building and Deploying Machine Learning Models

TensorFlow 2 Pocket Reference: Building and Deploying Machine Learning Models by KC Tung
English | August 10th, 2021 | ISBN: 1492089184 | 256 pages | True EPUB | 12.40 MB

This easy-to-use reference for TensorFlow 2 design patterns in Python will help you make informed decisions for various use cases. Author KC Tung addresses common topics and tasks in enterprise data science and machine learning practices rather than focusing on TensorFlow itself.