Jalaj Thanaki
Sr. Solution Architect, Gen AI at NVIDIA
Mumbai, Maharashtra, India
Summary
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Senior🎓
Top SchoolJalaj Thanaki is a senior solution architect and data scientist with 11 years of experience building NLP and generative AI products across publishing, finance, and research domains. Currently at NVIDIA after leading AI-driven academic editing and discovery tools at Cactus Labs (including contributions to Paperpal and Ask R Discovery), he blends production-grade engineering with research-driven approaches. He is the author of practical NLP and machine learning books and maintains the NLPython GitHub repo that accompanies his Python Natural Language Processing book. Technically fluent in Python, deep learning, big data stacks and secure generative AI, he has a track record of turning large scientific corpora into factual, validated answers. Colleagues know him as a hands-on mentor who moves ideas from prototyping to deployed systems. Based in Mumbai, he pairs strong academic credentials (M.Eng. Computer Engineering) with pragmatic startup and enterprise delivery experience.
10 years of coding experience
8 years of employment as a software developer
Gujarat Technological University
English, Gujarati, Hindi
Github Skills (12)
nltk10
tokenize10
tokenizer10
python10
natural-language-processing10
stemming9
lemmatization9
text-mining9
regular-expression8
feature-engineering5
deep-learning5
deeplearning-ai5
Programming languages (8)
Github contributions (5)
jalajthanaki/NLPython
Feb 2017 - Dec 2018
This repository contains the code related to Natural Language Processing using python scripting language. All the codes are related to my book entitled "Python Natural Language Processing"
Role in this project:
Data Scientist
Data ScientistContributions:112 commits, 3 PRs, 106 pushes in 1 year 10 months
Contributions summary:Jalaj contributed to the development of a Natural Language Processing (NLP) project using Python. The commits primarily involved setting up the NLTK environment, including installation and data downloads. Further contributions included code related to chapter 2 and 4 of the book, which likely involved basic corpus analysis, tokenization, stemming, lemmatization, and regular expressions. The user appears to be focusing on the practical application of NLP techniques in the context of their book.
part-of-speechpythonpython-scripting-languageprincipal-component-analysislanguage-processing
jalajthanaki/Get_Jobs_in_Data_Science
Sep 2018 - Sep 2018
Contributions:43 commits, 1 push, 1 branch in 2 days
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