Dipanjan (DJ) Sarkar (dipanjanS)

dipanjanS

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Dipanjan (DJ) Sarkar's repositories

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.

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:2242Issues:160Issues:31

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.

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:1638Issues:119Issues:14

hands-on-transfer-learning-with-python

Deep learning simplified by transferring prior learning using the Python deep learning ecosystem

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:823Issues:56Issues:8

tensorflow2-crash-course

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

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:227Issues:12Issues:0

data_science_for_all

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

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:203Issues:9Issues:3

nlp_essentials

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

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:171Issues:6Issues:1

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.

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:134Issues:10Issues:0

adversarial-learning-robustness

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

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:86Issues:4Issues:0

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

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:81Issues:9Issues:1

nlp_crash_course_plugin20

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

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:71Issues:10Issues:1

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

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:48Issues:4Issues:0

convolutional_neural_networks_essentials

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

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:43Issues:3Issues:0

nlp_workshop_odsc19

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

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:37Issues:3Issues:1

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

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:36Issues:5Issues:0

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

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:29Issues:5Issues:0

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.

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:26Issues:2Issues:0

practical_nlp_workshop_gids20

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

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:23Issues:3Issues:0

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

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:21Issues:2Issues:0

nlp_workshop_iisc19

Hands-on examples showcasing popular NLP applications

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:19Issues:3Issues:1

adversarial_learning_tfug2020

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

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:17Issues:2Issues:0

ml_model_deployment_example

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

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:10Issues:3Issues:0

appliedml_workshop_dhs_av_2019

Content for Applied ML Workshop @ DataHack Summit 2019

Language:Jupyter NotebookStargazers:6Issues:1Issues:0

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

Language:Jupyter NotebookLicense:AGPL-3.0Stargazers:5Issues:3Issues:0

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

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:4Issues:0Issues:0

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

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:3Issues:3Issues:0

duke-cloud-computing-for-data-coursera

Will contain all the necessary code examples for the Duke Cloud Computing Specialization on Coursera

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:3Issues:2Issues:0

satellite-image-super-resolution

This repository contains the end-to-end workflow consisting of code, models, methodologies and results of a joint-effort between South Pole and SIT Academy to build a Super Resolution Imaging System leveraging Deep Transfer Learning and Computer Vision for Satellite Imagery from Google Earth Engine to assess the impact of climate action interventions

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:2Issues:1Issues:0

awesome-transfer-learning

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

neural-structured-learning

Training neural models with structured signals.

Language:PythonLicense:Apache-2.0Stargazers:0Issues:1Issues:0

openshift-probable-vulnerabilities

This repository contains all the code, models, scripts and reports for flagging probable vulnerabilities for the gokube-openshift eco-system

License:GPL-3.0Stargazers:0Issues:1Issues:0