Deciphering human language using Machine Learning

Atul Singh (~atul98)




In this hands-on course using Python, we will learn how to use machine learning for Natural Language Processing (NLP) through interactive notebooks. Natural Language Processing (NLP) is a field that covers computer understanding and manipulation of human language. Machine learning is a branch of Artificial Intelligence that focuses on the ability to automatically learn from existing information. Language processing uses models that attempt to understand and represent the information at various levels that includes morphology, syntax, semantics, pragmatics and discourse. In this training, we will learn how to use machine learning to build these models.

This training includes the following topics:

  1. Representing text as a vector using count, TF-IDF and co-occurrence matrix
  2. Detecting similar documents
  3. Sentiment Analysis
  4. Identifying the themes in a set of documents
  5. Extracting the entities and the relationship between the entities (stretch goal depending on time)

The course will introduce the participants to NLP libraries such as nltk, gensim and Spacy.


This is an advanced machine learning course. To benefit from this course the participants are expected to have: 1. Understanding of supervised and unsupervised machine learning 2. Knowledge of python, or a high-level programming language like Java or C#. 3. Using jupyter Python notebook environment

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Speaker Info:

Atul Singh

Atul Singh is a data science enthusiast with over sixteen years of software industry work experience in product development, research, and innovation. He has a PhD in Computer Science. He has nine granted US patents, eleven pending US patent applications, and over fifteen research publications in various international forums. He is also an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Natural Language Processing (NLP), geo-spatial analytics, and reinforcement learning.

Sasidhar Donaparthi

I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company.

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Section: Data science
Type: Workshops
Target Audience: Intermediate
Last Updated:

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