Deep Learning in NLP - Powered by Python
Rishabh (~rishy) |
Deep Learning has recently gained lot of attention in academia as well as in industry. Although the most primitive concepts of artificial intelligence date back to 1960s-1970s, but with the advent of more powerful machines and even more elegant programming languages(of course Python), now it's possible to code a Deep Learning model in a very short time and with less hassle.
Natural Language Processing(NLP) has been a very important sub-field of AI and current state-of-the-art models employs deep neural networks, most of the time coupled with Python to quickly develop these rather complex networks. Some of the use cases of NLP is Language Modelling, Sentiment Analysis, Named Entity Recognition, Topic Modelling, Semantic Proximity, etc. In this workshop we'll create a Deep Learning Model(Recurrent Neural Network) for Language Modelling using Gensim Word2Vec and Theano. Gensim and Theano are both Python based libraries which makes it real easy to code Deep Neural Nets.
- Introduction to Neural Networks
- Word Vector Embeddings
- Introduction to Gensim
- Introduction to Theano
- What are Deep Learning Models?
- Recurrent Neural Networks
- What is a Language Model?
- A Language model with RNN and Theano
- Basic Python and Numpy
- Knowledge of Neural Networks
Required Setup for the Workshop
- Install "Conda" as suggested at: https://www.continuum.io/downloads
- conda install theano
- conda install gensim
- Download this pre-cleaned wikipedia articles file: Google Drive Link
I am the Platform Head and Chief Deep Learning Engineer at Neuron, a Natural Language Processing/Machine Learning startup. I am also a FOSS supporter and have been a GSOC Intern for Mifos Initiative in the year 2014.
Email - [email protected]
Phone - +917838742284