Dipanjan (DJ) Sarkar

practical-machine-learning-with-python. 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.

text-analytics-with-python. 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.

hands-on-transfer-learning-with-python. Deep learning simplified by transferring prior learning using the Python deep learning ecosystem

training-fine-tuning-large-language-models-workshop-dhs2024. This repository will contain all the presentations, content, hands-on notebooks for a full day Generative AI workshop on Training, Fine-tuning Large Language Models for the DataHack Summit 2024 conference.

tensorflow2-crash-course. A quick crash course in understanding the essentials of TensorFlow 2 and the integrated Keras API

data_science_for_all. Code and resources for my blog and articles to share Data Science and AI knowledge and learnings with everyone

mastering-intelligent-agents-langgraph-workshop-dhs2025. This repository will contain all the presentations, content, hands-on python notebooks for a full day Agentic AI workshop on Building Simple and Complex Agents, Deploying and Monitoring AI Agents with LangGraph for the DataHack Summit 2025 conference.

nlp_essentials. Essential and Fundametal aspects of Natural Language Processing with hands-on examples and case-studies

art_of_data_visualization. The art of effective visualization of multi-dimensional data

nlp_workshop_odsc_europe20. Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage machine learning, deep learning and deep transfer learning to learn and solve popular tasks using NLP including NER, Classification, Recommendation \ Information Retrieval, Summarization, Classification, Language Translation, Q&A and Topic Models.

learning-social-media-analytics-with-r. This repository contains code and bonus content which will be added from time to time for the book "Learning Social Media Analytics with R" by Packt

improving-RAG-systems-dhs2024. This repository will contain the presentation and python jupyter notebooks for the DataHack Summit 2024 conference talk, Improving Real-world Retrieval Augmented Generation Systems, focusing on the key challenges and practical solutions of how to solve them

BerkeleyX-CS100.1x-Big-Data-with-Apache-Spark. This repository contains code files specifically IPython notebooks for the assignments in the course "Introduction to Big Data with Apache Spark" by UC Berkeley and Databricks on edX

adversarial-learning-robustness. Contains materials for workshops pertaining to adversarial robustness in deep learning.

deep_transfer_learning_nlp_dhs2019. Contains the code and deck for the presentation on Applying Deep Transfer Learning for NLP in Analytics Vidhya's DataHack Summit 2019

building-effective-agentic-ai-systems-dhs2025. This repository will contain the presentation and python jupyter notebooks for my DataHack Summit 2025 conference talk, Building Effective Agentic AI Systems: Lessons from the Field. Drawing from my experience building deploying Agentic AI systems, we’ll focus on three pillars: Architecting, Optimizing, and Observability for Agentic AI Systems.

nlp_crash_course_plugin20. Contains relevant notebooks for the hands-on NLP workshop for the Analytics India Magazine Plugin Conference -2020 Edition

nlp_workshop_dhs18. Contains code and presentation for our full day workshop, 'Getting Started with Natural Language Processing'. This is created for the purpose of being presented in Analytics Vidhya's DataHack Summit 2018. Authors: Dipanjan Sarkar & Raghav Bali

adv_nlp_workshop_odsc_europe22. Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage deep learning and deep transfer learning to solve popular tasks in NLP including Classification, Information Retrieval, Sentiment Analysis, Search Engines, Clustering, Paraphrase Mining, Summarization, Language Translation, Q&A systems

convolutional_neural_networks_essentials. Contains presentation deck and notebooks showcasing fundamental concepts and hands-on examples for Convolutional Neural Networks

nlp_workshop_odsc19. Contains all tutorials and hands-on examples for the ODSC 2019 Workshop

live-manning-nlpconf20. Papers, code and slides for my session at the live@manning NLP conference, 2020 covering my talk on Deep Transfer Learning for Natural Language Processing

explainable_artificial_intelligence. Slides, code and resources for model interpretation methods in machine learning and deep learning

BerkeleyX-CS190.1x-Scalable-Machine-Learning. This repository contains code files specifically IPython notebooks for the assignments in the course "Scalable Machine Learning" by UC Berkeley and Databricks on edX

feature_engineering_session_dhs18. Contains code and presentation for my interactive hack session, 'Effective Feature Engineering: A Structured Approach to Building Better Machine Learning Models' where we look at two interesting case studies on how to effectively leverage feature engineering and use a structured approach to build good machine learning models. This is created for the purpose of being presented in Analytics Vidhya's DataHack Summit 2018

transformers_nlp_essentials. Contains slides and hands-on tutorials for understanding and implementing Transformers in Natural Language Processing. Uses the HuggingFace Transformers framework in the hands-on tutorials.

practical_nlp_workshop_gids20. Contains relevant notebooks for the hands-on NLP workshop for the GIDS AIML Conference -2020 Edition

low_code_machine_learning_pycaret_workshop_2022. This workshop was done as a part of the 1729 conference organized by Fractal Analytics and Analytics Vidhya. Key content covered was hands-on notebooks leveraging PyCaret to compare, build, tune, evaluate and interpret machine learning models

nlp_workshop_iisc19. Hands-on examples showcasing popular NLP applications

adversarial_learning_tfug2020. Contains the slides and hands-on tutorials showcasing adversarial learning on convolutional neural networks to build robust vision models

stanford-statistical-learning. Slides, material and solutions of the popular Statistical Learning course from Stanford's own Hastie & Tibshirani. Join me on my journey to finally try and complete this course after leaving it mid-way atleast 3-4 times due to other commitments!

MyShinyApps. Shiny is a web application framework for R. This repo contains all the web apps developed by me using R and Shiny.

ml_model_deployment_example. A simple example to showcase machine learning model deployment with an API

Digital-image-steganography. This project successfully implements an encoder-decoder system where we can hide a secret image inside another image and retrieve it secretly later using the decoder only.

awesome-public-datasets. A awesome list of (large-scale) public datasets on the Internet. (On-going collection)

appliedml_workshop_dhs_av_2019. Content for Applied ML Workshop @ DataHack Summit 2019

adv_nlp_workshop_odsc_europe23. Extensive tutorials for the Advanced NLP Session in Open Data Science Conference Europe 2023. We will leverage deep transfer learning, notably transformers to solve popular tasks in NLP including Classification, Information Retrieval, Sentiment Analysis, Search Engines, Clustering, Paraphrase Mining, Summarization, Language Translation, Q&A systems

parallel_ml_tutorial. Tutorial on scikit-learn and IPython for parallel machine learning

adv_nlp_workshop_odsc_apac2323. Extensive tutorials for the Advanced NLP Session in Open Data Science Conference APAC 2023. We will leverage deep transfer learning, notably transformers and LLMs like ChatGPT to solve popular tasks in NLP including Classification, Information Retrieval, Sentiment Analysis, Search Engines, Summarization, Language Translation, Q&A systems

flask-api-tutorials. This repository contains the RESTful APIs developed showing the capabilites of Flask and how to modularize the same code using some advanced features of Flask

deeplearning.ai-generative-ai-courses. This repository will contain all the exercises, tutorials and python jupyter notebooks for all the DeepLearning.AI courses on Generative AI, ChatGPT, LangChain, LLMs and more

student-information-system. This project has an entire template for managing students and related information pertaining to them in any University.

awesome-deep-learning. A curated list of awesome Deep Learning tutorials, projects and communities.

python-patterns. A collection of design patterns/idioms in Python

duke-cloud-computing-for-data-coursera. Will contain all the necessary code examples for the Duke Cloud Computing Specialization on Coursera

Temperature-Aware-Linux. A temperature-aware application for creating a temperature-aware variant of the linux OS

text-analytics-python-improvements. This is a temporary repository for working on improvements for my book 'Text Analytics with Python'

tensorflow-gpu-install-ubuntu-16.04. Tensorflow GPU install instructions for ubuntu 16.04

dipanjanS.github.io.old. Build a Jekyll blog in minutes, without touching the command line.

awesome-python. A curated list of awesome Python frameworks, libraries and software.

awesome-transfer-learning. Best transfer learning and domain adaptation resources (papers, tutorials, datasets, etc.)

prose. A Content Editor for GitHub.

awesome-machine-learning. A curated list of awesome Machine Learning frameworks, libraries and software.

practicalML-course-project. This detailed analysis has been performed to fulfill the requirements of the course project for the course Practical Machine Learning offered by the Johns Hopkins University on Coursera

python-cookbook. Code samples from the "Python Cookbook, 3rd Edition", published by O'Reilly & Associates, May, 2013.