Notes:
Deep learning is a subfield of machine learning that is inspired by the structure and function of the brain, specifically the neural networks that make up the brain. It involves training artificial neural networks on a large dataset, allowing the network to learn and make intelligent decisions on its own.
Natural language processing (NLP) is a subfield of artificial intelligence that deals with the interaction between computers and human (natural) languages. NLP allows computers to read, understand, and generate human-like language, which is crucial for tasks such as language translation, text summarization, and text classification.
Deep learning has played a significant role in the development of NLP, particularly in the last decade. Many of the most successful NLP models today, such as those used for language translation and text classification, are based on deep learning techniques. These models are able to handle large amounts of data, automatically extract relevant features from the data, and make predictions with high accuracy.
See also:
100 Best Natural Language Generation Videos | 100 Best Natural Language Parsing Videos | 100 Best Natural Language Processing Tutorial Videos | 100 Best Natural Language Understanding Videos
- Module 11, Part 3: Applications of Deep Learning: NLP &Word2Vec
- Module 11, Part 2: Applications of Deep Learning: NLP & End to End Network
- Module 11, Part 1: Applications of Deep Learning: Chat Bots & NLP
- Yves Peirsman on ‘Deep Learning for NLP’ at Sentiance
- What is Deep Learning, Natural Language Processing and Machine Learning? @salesforce ? @jimsinai ?
- Deep Learning & NLP – Deriving intent from spoken information
- useR! International R User 2017 Conference Deep Learning for Natural Language Processing in R
- Deep Learning for Natural Language Processing by Roopal Garg
- Jason Weston: Deep Learning for Natural Language Processing
- Study Group Le Mans – NLP – Deep Learning – Machine Learning
- Lecture 18: Tackling the Limits of Deep Learning for NLP
- Lecture 1 | Natural Language Processing with Deep Learning
- Lukasz Kaiser at AI Frontiers: How Deep Learning Quietly Revolutionized NLP
- Lecture 1 | Natural Language Processing with Deep Learning
- Lecture 1 | Natural Language Processing with Deep Learning
- How we are building serverless architectures for Deep Learning & NLP at Episource: Manas Ranjan Kar
- Augmenting Solr’s NLP Capabilities with Deep-Learning Features to Match Images: Kumar Shubham
- Anshul Ravichandar – Introduction to NLP in Deep Learning
- Deep Learning for Natural Language Processing – Richard Socher, Salesforce
- Tech 2025 Workshop: AI, Machine Learning, NLP, and Deep Learning
- Rob Romijnders | Using deep learning in natural language processing
- RobotX Workshop: Deep learning + Security + NLP With UC Berkeley AI Lab
- Lecture 18: Tackling the Limits of Deep Learning for NLP
- Lecture 1 | Natural Language Processing with Deep Learning
- Deep Learning for Natural Language Processing
- Tutorial – Natural Language Processing for Music Information Retrieval. Deep Learning
- Joelle Pineau – Deep learning models for natural language interaction
- Deep Learning for NLP – Lecture 3
- Deep Learning for Natural Language Processing
- Natural Language Processing with Deep Learning in Python Udemy
- Deep Learning for Natural Language Processing in Python Intro
- Deep Learning Natural Language Processing in Python with GLoVe From Word2Vec to GLoVe in Python and
- Deep Learning Natural Language Processing in Python with Recursive Neural Networks Recursive Neural
- Empirical Methods in NLP (Lecture 8: Deep learning, neural word association)
- Deep Learning Natural Language Processing in Python with GLoVe From Word2Vec to GLoVe in Python and
- Deep Learning Natural Language Processing in Python with Recursive Neural Networks Recursive Neural
- Deep Learning Natural Language Processing in Python with Recursive Neural Networks Recursive Neural
- Professor Qun Liu – Deep Learning for NLP: Myth or Opportunity?
- Deep Learning and NLP by Salesforce, LinkedIn, Baidu and VentureBeat
- Deep Learning for Natural Language Processing Richard Socher, Salesforce
- [NUS CS 6101 Deep Learning for NLP] – Week 10 – Recursive Neural Networks (RNNs)
- deep learning nlp tutorial
- deep learning for nlp
- deep learning for nlp
- deep learning for nlp
- deep learning for nlp
- deep learning for nlp
- datascience@berkeley | Natural Language Processing with Deep Learning
- deep learning nlp tutorial
- Deep Learning for Natural Language Processing (Richard Socher, Salesforce)
- [NUS CS 6101 Deep Learning for NLP]
- Deep Learning: Natural Language Processing in Python
- Overview: NLP & Deep Learning
- Deep Learning and NLP with Spark by Andy Petrella and Melanie Warrick
- Deep Learning and NLP with Spark – by Andy Petrella
- Raghotham Sripadraj & Nischal HP – Introduction to Deep Learning & Natural Language Processing
- Deep Learning in NLP – Powered by Python
- Deep Learning in NLP – Powered by Python
- Deep Learning for Question Answering – DC NLP
- DArViN ’15: Introduction to Deep Learning for NLP by Wojciech Zar?ba (part 1/6)
- DArViN ’15: Advances in Deep Learning for NLP by Wojciech Zar?ba (part 2/6)
- Deep Learning for NLP – Lecture 6 – Recurrent Neural Network
- Deep Learning for NLP – Lecture 5 – Convolutional Neural Networks
- Image Annotation – The Marriage of Computer Vision and NLP Using Deep Learning – Prof. Lior Wolf
- Deep Learning for NLP – Lecture 4 – Autoencoders
- Deep Learning for NLP – Lecture 3
- Deep Learning for NLP – Lecture 2
- Deep Learning for NLP – Lecture 1
- Jason Weston: “Deep Learning for Natural Language Processing”
- Deep Learning in Natural Language Processing – Sebastian Ebert
- Devashish Shankar – Deep Learning for Natural Language Processing
- Martin Goodson – building NLP learning systems using deep learning and Apache Spark
- Text By the Bay 2015: Richard Socher, Deep Learning for Natural Language Processing
- Text By the Bay 2015: Adam Gibson, NLP And Deep Learning: Working with Neural Word Embeddings
- Deep Learning for NLP in Bulgarian
- NLP and Deep Learning: introduction – Session I
- Natural Language Processing with Deep Learning
- Deep Learning for NLP without Magic (Part 2)
- Deep Learning for NLP without Magic (Part 1)
- Deep Learning for NLP without Magic Part 2
- Deep Learning for NLP without Magic Part 1
- Deep Learning for NLP (without Magic) – Part 9
- Deep Learning for NLP (without Magic) – Part 10
- Deep Learning for NLP (without Magic) – Part 8
- Deep Learning for NLP (without Magic) – Part 7
- Deep Learning for NLP (without Magic) – Part 6
- Deep Learning for NLP (without Magic) – Part 4
- Deep Learning for NLP (without Magic) – Part 3
- Deep Learning for NLP (without Magic) – Part 2
- Deep Learning for NLP (without Magic) – Part 1
- Deep Learning for NLP (without Magic) – Part 11
- Deep Learning for NLP (without Magic) – Part 5