Nazim Shaikh (nazim1021)

nazim1021

Geek Repo

Company:Roche

Location:Santa Clara, California, United States

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Nazim Shaikh's repositories

OOD-detection-using-OECC

Outlier Exposure with Confidence Control for Out-of-Distribution Detection

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neural-machine-translation-using-gan

Application of rnn-gan to machine translation

multimodal-lip-reading

Lip reading in the wild using CNN-LSTM

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text-detection-and-recognition

Parsing text data in images using opencv and EAST algorithm

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data-science-ipython-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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deep-learning

Deep learning portfolio

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digital-image-processing

Projects as part of digital image processing coursework

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machine-learning

Machine learning portfolio

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deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

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deep-learning-with-pytorch

Experimental notebooks from Udacity's Deep Learning with PyTorch Lesson

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examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

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fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

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flair

A very simple framework for state-of-the-art Natural Language Processing (NLP)

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ML_paper_notes

:book: Notes and summaries of some Machine Learning / Computer Vision / NLP papers.

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mosesdecoder

Moses, the machine translation system

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NoteBooks-Statistics-and-MachineLearning

Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog

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python-machine-learning-book-2nd-edition

The "Python Machine Learning (2nd edition)" book code repository and info resource

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Tensorflow-2.0

Crash course on TensorFlow 2.0

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TensorFlow-Examples

TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

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tensorhub

TensorHub is a library of deep learning models and lego like interlocking blocks designed to make deep learning more accessible and accelerate ML research using TensorFlow 2.0

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VASNet

PyTorch implementation of the ACCV 2018-AIU2018 paper Video Summarization with Attention

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