Dipanjan Sarkar
Head Of Artificial Intelligence & Community at Analytics Vidhya
India
Summary
🤩
Rockstar
Top expert inQuantitative Finance and Algorithmic Trading with Machine Learning
Dipanjan Sarkar is a Principal AI Scientist and Head of Artificial Intelligence & Community with 13+ years of experience building and leading AI, ML, NLP and Generative/Agentic AI initiatives across startups and Fortune 100 companies. He combines hands-on engineering—authoring popular open-source repos and books on text analytics, transfer learning and practical ML—with strategic leadership in building global upskilling programs and corporate AI products. As a Google Developer Expert and multi-time industry awardee, he has advised and trained thousands of professionals and led cross-continental projects spanning APAC, EMEA and the Americas. Notably, he has delivered early Generative AI solutions and one of the first comprehensive commercial Generative AI curricula in Europe, while also generating over $1M as an independent consultant. He focuses on community-first collaborations and practical deployments that translate advanced research into usable data products.
13 years of coding experience
10 years of employment as a software developer
Github Skills (28)
gensim10
python10
matplotlib10
scikit10
nltk10
machine-learning10
text-analytics10
numpy10
linear-regression10
mask-rcnn10
keras10
natural-language-processing10
scikit-learn10
faster-rcnn10
jupyter-notebook10
Programming languages (7)
Github contributions (5)
dipanjanS/practical-machine-learning-with-python
Jul 2017 - Sep 2018
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
Role in this project:
Data Scientist
Data ScientistContributions:130 commits, 2 PRs, 112 pushes in 1 year 1 month
Contributions summary:Dipanjan contributed code and content related to chapter 1. Based on the code differences and commit messages the user added content for chapter 1, which included examples of natural language processing, mathematical and statistical examples. The commit included several examples of code for building a parse tree from sentences, along with the visualization. It also contained the use of various libraries such as `nltk`, `matplotlib`, and `numpy`.
pythondata-preprocessingk-meansecosift
dipanjanS/text-analytics-with-python
Sep 2016 - Dec 2020
Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.
Role in this project:Data Scientist
Data ScientistContributions:64 commits, 3 PRs, 59 pushes in 4 years 3 months
Contributions summary:Dipanjan's commits primarily involve adding code files that explore various aspects of text analytics using Python. These contributions include demonstrations of core NLP concepts, such as tokenization, stemming, lemmatization, and sentiment analysis. The user also implements and showcases several document clustering and topic modeling techniques. Furthermore, code examples for feature extraction are provided.
pythonword-embeddingssemanticstopic-modelingspringer
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