Your cart is currently empty!
Advanced Natural Language Processing with TensorFlow 2: Build effective real-world NLP applications using NER, RNNs, seq2seq models, Transformers, and more
![](https://ziontechgroup.com/wp-content/uploads/2024/12/71MswSybzcL._SL1360_.jpg)
Price: $42.27
(as of Dec 26,2024 22:41:02 UTC – Details)
From the brand
Packt is a leading publisher of technical learning content with the ability to publish books on emerging tech faster than any other.
Our mission is to increase the shared value of deep tech knowledge by helping tech pros put software to work.
We help the most interesting minds and ground-breaking creators on the planet distill and share the working knowledge of their peers.
New Releases
LLMs and Generative AI
Machine Learning
See Our Full Range
Publisher : Packt Publishing (February 3, 2021)
Language : English
Paperback : 380 pages
ISBN-10 : 1800200935
ISBN-13 : 978-1800200937
Item Weight : 1.45 pounds
Dimensions : 9.25 x 7.52 x 0.79 inches
Are you ready to take your Natural Language Processing skills to the next level? Join us in our upcoming workshop on Advanced Natural Language Processing with TensorFlow 2.
In this workshop, we will dive deep into building effective real-world NLP applications using cutting-edge techniques such as Named Entity Recognition (NER), Recurrent Neural Networks (RNNs), sequence-to-sequence models, Transformers, and more.
Whether you are a seasoned NLP practitioner looking to expand your toolkit or a beginner eager to learn the latest advancements in the field, this workshop is for you. Our experienced instructors will guide you through hands-on exercises and practical examples to help you master these advanced NLP concepts.
Don’t miss this opportunity to sharpen your NLP skills and stay ahead of the curve. Register now for our Advanced Natural Language Processing with TensorFlow 2 workshop and unlock the full potential of NLP in your projects.
#Advanced #Natural #Language #Processing #TensorFlow #Build #effective #realworld #NLP #applications #NER #RNNs #seq2seq #models #Transformers
Leave a Reply