Ronald Kneusel Math For Deep Learning
Math for Deep Learning: What You Need to Know to Understand Neural Networks eBooks & eLearning
Posted by yoyoloit at June 30, 2022
Math for Deep Learning
by Ronald T. Kneusel
English | 2022 | ISBN: 1718501900 | 347 pages | True PDF MOBI | 59.18 MB
by Ronald T. Kneusel
English | 2022 | ISBN: 1718501900 | 347 pages | True PDF MOBI | 59.18 MB
Math for Deep Learning: What You Need to Know to Understand Neural Networks eBooks & eLearning
Posted by First1 at Nov. 23, 2021
Math for Deep Learning: What You Need to Know to Understand Neural Networks by Ronald T. Kneusel
English | December 7th, 2021 | ISBN: 1718501900 | 344 pages | True EPUB | 25.46 MB
English | December 7th, 2021 | ISBN: 1718501900 | 344 pages | True EPUB | 25.46 MB
Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the deep learning toolkits.
Practical Deep Learning: A Python-Based Introduction eBooks & eLearning
Posted by yoyoloit at Sept. 24, 2021
Practical Deep Learning
by Ronald T. Kneusel
English | 2021 | ISBN: 1718500742 | 464 pages | True PDF | 13.59 MB
by Ronald T. Kneusel
English | 2021 | ISBN: 1718500742 | 464 pages | True PDF | 13.59 MB
How AI Works: From Sorcery to Science eBooks & eLearning
Posted by Free butterfly at Feb. 10, 2024
How AI Works: From Sorcery to Science by Ronald T. Kneusel
English | October 24, 2023 | ISBN: 1718503725 | 192 pages | PDF | 5.54 Mb
English | October 24, 2023 | ISBN: 1718503725 | 192 pages | PDF | 5.54 Mb
How AI Works: From Sorcery to Science eBooks & eLearning
Posted by First1 at Oct. 24, 2023
How AI Works: From Sorcery to Science by Ronald T. Kneusel
English | October 24th, 2023 | ISBN: 1718503725 | 192 pages | True EPUB (Retail Copy) | 19.05 MB
English | October 24th, 2023 | ISBN: 1718503725 | 192 pages | True EPUB (Retail Copy) | 19.05 MB
AI isn’t magic. How AI Works demystifies the explosion of artificial intelligence by explaining—without a single mathematical equation—what happened, when it happened, why it happened, how it happened, and what AI is actually doing "under the hood."