Fun uses for word vectors.
Explore how to move words from inflammatory to less inflammatory with word vectors.
| Format: | Video |
|---|---|
| Language: | English |
| Published: |
[Place of publication not identified] :
Manning Publications,
[2020]
|
| Edition: | [First edition]. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Similar Items
Introduction to transformer models for NLP : using BERT, GPT, and more to solve modern natural language processing tasks.
Published: (2022)
Published: (2022)
Real-world natural language processing /
by: Hagiwara, Masato
Published: (2022)
by: Hagiwara, Masato
Published: (2022)
Introduction to transformers for NLP : with the Hugging Face library and models to solve problems /
by: Jain, Shashank Mohan
Published: (2022)
by: Jain, Shashank Mohan
Published: (2022)
Natural language processing - NLP 2000 : Second International Conference, Patras, Greece, June 2-4, 2000 : proceedings /
Published: (2000)
Published: (2000)
Use PyNNDescent and `nessvec` to index high dimensional vectors (word embeddings).
Published: (2022)
Published: (2022)
Natural language processing and information systems : 5th International Conference on Applications of Natural Language to Information Systems, NLDB 2000, Versailles, France, June 28-30, 2000 : revised papers /
Published: (2001)
Published: (2001)
Natural language processing and information systems : 6th International Conference on Applications of Natural Language to Information Systems, NLDB 2002, Stockholm, Sweden, June 27-28, 2002 : revised papers /
Published: (2002)
Published: (2002)
Real-World Natural Language Processing: Practical applications with deep learning.
by: Hagiwara, Masato
Published: (2021)
by: Hagiwara, Masato
Published: (2021)
Natural language processing /
Published: (2021)
Published: (2021)
Adding large files for NL datasets.
Published: (2022)
Published: (2022)
Linguistics for the age of AI /
by: McShane, Marjorie Joan, 1967-, et al.
Published: (2021)
by: McShane, Marjorie Joan, 1967-, et al.
Published: (2021)
Machine reading comprehension : algorithms and practice /
by: Zhu, Chenguang (Computer scientist)
Published: (2021)
by: Zhu, Chenguang (Computer scientist)
Published: (2021)
Integration of Natural Language and Vision Processing.
Published: (1996)
Published: (1996)
Integration of Natural Language and Vision Processing. Theory and Grounding Representations /
Published: (1996)
Published: (1996)
Extreme summarization with FastText word embeddings and RoBERTa encodings.
Published: (2022)
Published: (2022)
Getting started with natural language processing /
by: Kochmar, Ekaterina
Published: (2022)
by: Kochmar, Ekaterina
Published: (2022)
AI superstream : NLP in production /
Published: (2022)
Published: (2022)
Mian xiang zi ran yu yan chu li de shen du xue xi ke cheng : shen du shen jing wang luo zai ji qi xue xi ren wu de ying yong.
Published: (2017)
Published: (2017)
Train Word embeddings from scratch with Nessvec and PyTorch.
Published: (2022)
Published: (2022)
Aspects of automated natural language generation : 6th International Workshop on Natural Language Generation, Trento, Italy, April 5-7, 1992 : proceedings /
Published: (1992)
Published: (1992)
Natural language processing with TensorFlow : the definitive NLP book to implement the most sought-after machine learning models and tasks /
by: Ganegedara, Thushan
Published: (2022)
by: Ganegedara, Thushan
Published: (2022)
Logic, language and computation /
Published: (1997)
Published: (1997)
TEACHING COMPUTERS TO READ : effective best practices in building valuable nlp solutions.
by: WAGNER-KAISER, RACHEL
Published: (2025)
by: WAGNER-KAISER, RACHEL
Published: (2025)
Create a dialog engine or finite state machine (FSM).
Published: (2022)
Published: (2022)
Natural language processing mit PyTorch : Intelligente Sprachanwendungen mit Deep Learning erstellen /
by: Rao, Delip, et al.
Published: (2020)
by: Rao, Delip, et al.
Published: (2020)
NLP in action : attention mechanism and upgrading TorchText 0.9.
by: Lane, Hobson
Published: (2022)
by: Lane, Hobson
Published: (2022)
Deep learning for natural language processing /
by: Raaijmakers, Stephan
Published: (2022)
by: Raaijmakers, Stephan
Published: (2022)
ACM transactions on Asian and low-resource language information processing.
Published: (2015)
Published: (2015)
Natural language processing projects : build next -generation NLP applications using AI techniques /
by: Kulkarni, Akshay, et al.
Published: (2022)
by: Kulkarni, Akshay, et al.
Published: (2022)
Cognitive approach to natural language processing /
Published: (2017)
Published: (2017)
Computing with words in information/intelligent systems /
Published: (1999)
Published: (1999)
Natural language processing with transformers : building language applications with Hugging Face /
by: Tunstall, Lewis, et al.
Published: (2023)
by: Tunstall, Lewis, et al.
Published: (2023)
Controlled document authoring in a machine translation age /
by: Miyata, Rei
Published: (2021)
by: Miyata, Rei
Published: (2021)
Deep learning and linguistic representation /
by: Lappin, Shalom
Published: (2021)
by: Lappin, Shalom
Published: (2021)
How to be happy with a Chatbot state machine.
Published: (2022)
Published: (2022)
Generalized LR Parsing /
by: Tomita, Masaru
Published: (1991)
by: Tomita, Masaru
Published: (1991)