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kruthika kr's Projects

artificial-intelligence-deep-learning-machine-learning-tutorials icon artificial-intelligence-deep-learning-machine-learning-tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by Tarry Singh until at-least 2020 until he finishes his Ph.D. (which might end up being inter-stellar cosmic networks! Who knows! πŸ˜€)

awesome-ai-books icon awesome-ai-books

Some awesome AI related books and pdfs for learning and downloading, also apply some playground models for learning

awesome-autodl icon awesome-autodl

A curated list of automated deep learning (including neural architecture search and hyper-parameter optimization) resources.

awesome-semantic-search icon awesome-semantic-search

A curated list of awesome resources related to Semantic SearchπŸ”Ž and Semantic Similarity tasks.

bootleg icon bootleg

Self-Supervision for Named Entity Disambiguation at the Tail

capsule-networks icon capsule-networks

A PyTorch implementation of the NIPS 2017 paper "Dynamic Routing Between Capsules".

chexnet-implementation-in-keras icon chexnet-implementation-in-keras

This is a reimplementation of CheXNet using Python3 and Keras. CheXNet, is a 121-layer convolutional neural network that inputs a chest X-ray image and outputs the probability of pneumonia along with a heatmap localizing the areas of the image most indicative of pneumonia.

cnn icon cnn

Convolutional Neural Networks - Stanford CS231n Course by Andrej Karpathy and Serena Yeung

data-science icon data-science

Collection of useful data science topics along with code and articles

data-science-ipython-notebooks icon data-science-ipython-notebooks

Recently updated with 50 new notebooks! Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

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