Deep Learning from the Basics eBook – Deep learning is fast gaining popularity as a method for solving data challenges.
This is partly due to the complexity of its mathematical algorithms and their capacity to detect patterns that are normally unseen to us.
Koki Saitoh’s Deep Learning from the Basics, published by Packt, is available for free (regular price $27.99). This limited-time offer is valid until November 24, 2021.
To obtain the ebook for free, visit TradePub’s giveaway page.
Complete all the essential fields in the form, such as your name and email address, or sign in with your LinkedIn credentials, then click the “Download” button.
This ebook is approximately 12.3 MB in size and contains 317 pages.
About Deep Learning from the Basics :
As technology progresses, what was formerly considered science fiction becomes more plausible—and, in some cases, realistic. Artificial intelligence has beaten champions in shogi, chess, and even Igo.
Smartphones are capable of comprehending human speech, and video calls enable real-time machine translation. Human lives are protected by “no-crash” cars equipped with built-in cameras, and automated vehicles are getting closer to practical use.
When we look around, we see that artificial intelligence accomplishes flawlessly what we previously believed were uniquely human tasks—at times even surpassing us. The advancement of artificial intelligence is reshaping and remaking our reality.
“Deep learning” technology is critical to such extraordinary advancements.
Globally recognised researchers hail deep learning as a new technique, even referring to it as a once-in-a-decade breakthrough. The phrase is now as well-known among the general public as it is among scientists and engineers.
This book focuses on deep learning, a topic that has gotten a lot of attention recently. The objective is for readers to gain a thorough understanding of deep learning technologies.
This book begins with a brisk introduction to deep learning with Python, including its definition, characteristics, and applications.
You’ll discover how to include the Python interpreter and script files into your apps, as well as how to use NumPy and Matplotlib into your deep learning models.
By the end of the book, you will be equipped with the knowledge necessary to apply important technologies to deep learning.