Mathusuthan Kannan's repositories

MIT_OCW_Linear_Algebra_18_06

IPython notebooks on Gilbert Strang's MIT course on linear algebra (18.06)

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anlp19

Course repo for Applied Natural Language Processing (Spring 2019)

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clean-code-ml

:bathtub: Clean Code concepts adapted for machine learning and data science. Now a free video series 😎 https://bit.ly/2yGDyqT

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cookiecutter-ds-template

A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.

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course-gitbook

Full Stack Deep Learning Course

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coursera-ds-algorithms

Codes and notes from UCSD's Data Structures and Algorithms Specialization on Coursera

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Coursera_Reinforcement_Learning

Coursera Reinforcement Learning Specialization by by University of Alberta & Alberta Machine Intelligence Institute

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cs229-ps-2018

My solutions to the problem sets of Stanford cs229, 2018

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deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

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deepar

Tensorflow implementation of Amazon DeepAR

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deepLearningBook-Notes

Notes on the Deep Learning book from Ian Goodfellow, Yoshua Bengio and Aaron Courville (2016)

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DL_Topics

List of DL Topics and resources essential for cracking interviews

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DLFS_code

Code for the book Deep Learning From Scratch, from O'Reilly September 2019

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gluon-nlp

NLP made easy

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grokking-system-design

Thanks to lirenTu@scale

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instance_level_recognition

The 2nd place solution to the 2020 edition of the Google Landmark Recognition competition

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just-blog

Contents for my site https://mathusuthan.com

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keras-idiomatic-programmer

Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework

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lessons

📚 Learn ML with clean code, simplified math and illustrative visuals. As you learn, work on interesting projects and share them on https://madewithml.com for the community to discover and learn from!

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nn4nlp-code

Code Samples from Neural Networks for NLP

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random-forest-importances

Code to compute permutation and drop-column importances in Python scikit-learn random forests

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recsys2019

The complete code and notebooks used for the ACM Recommender Systems Challenge 2019

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Reinforcement-Learning-Specialization

[Coursera] Reinforcement Learning Specialization by "University of Alberta" & "Alberta Machine Intelligence Institute"

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rosetta_recsys2019

The 4th Place Solution to the 2019 ACM Recsys Challenge by Team RosettaAI

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seai

CMU 17-445/645: Software Engineering for AI-Enabled Systems

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starry-nights

My Personal Web Site

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streamlit-launchpad

Browse a folder containing multiple streamlit apps and launch them immediately

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training-data-analyst

Labs and demos for courses for GCP Training (http://cloud.google.com/training).

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