Natural Language Processing (NLP) is a field in Artificial Intelligence enabling computers to understand natural (human) language. Natural language is difficult to handle especially when we have sarcasm, slang, different dialects,
and flexible rules.
The program is designed to provide theoretical and practical knowledge of state-of-the-art NLP applications through hands-on sessions on traditional and deep learning algorithms using appropriate packages such as NLTK, Spacy, Scikit-learn, TensorFlow/Keras, etc.
- Introduce Natural Language Processing (text data) and its applications.
- Learn the pre-processing steps and text representation for Feature Engineering.
- Learn how to handle large documents (big data).
- Learn Bag-of-words, TF-IDF Vectorization, N-Grams, Word Embeddings – One-hot, frequency-based, co-occurrence; prediction-based.
- Learn to build pipelines for NLP processing.
- Learn deep learning — Convolution Neural Network (CNN) and Recurrent Neural Network (RNN) – LSTM and GRU.
- Understand Word2Vec (CBOW and Skip-gram) and GloVe.
- Implement NLP Applications using state-of-the-art techniques:
- Topic Modeling – Understand techniques such as Latent Semantic Analysis/Truncated SVD, Non-negative Matrix Factorization & implement them for Document Clustering.
Who can Attend?
Working professionals, academicians and students with basic knowledge of machine learning and exposure to any programming language, preferably Python. It will also benefit participants already working in Business Analytics/Data Science domain to understand real-life applications of state-of-the-art NLP techniques.
- Early Bird – INR 8,500 plus GST @ 18%
- Regular – INR 9,500 plus GST @ 18%
- Fee includes program kit, the textbook on Machine Learning authored by U Dinesh Kumar, training material, lunch & refreshments for 2 days.
- Interested candidates can register online by clicking here.
- A certification of participation co-signed by CHRIST (Deemed to be University) and Analytics Society of India will be issued to participants who attend the complete duration of the MDP.
Phone Number: +91 80 2699 3822
Email ID: email@example.com