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Julie Gi's Projects

caffe icon caffe

Caffe: a fast open framework for deep learning.

courses icon courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

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.

deep-learning-book icon deep-learning-book

Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"

deeplearntoolbox icon deeplearntoolbox

Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.

face_recognition icon face_recognition

The world's simplest facial recognition api for Python and the command line

flair icon flair

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

h2o-3 icon h2o-3

Open Source Fast Scalable Machine Learning API For Smarter Applications (Deep Learning, Gradient Boosting, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA...)

mxnet icon mxnet

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

nuevotrabajo icon nuevotrabajo

GitHub repository for AWS CodeStar Python web service nuevotrabajo.

nyt-comments icon nyt-comments

A python module that retrieves comments from the New York Times articles customized with respect to timeline and queries and return the comments' and articles' data as pandas dataframes with an option to store it as csv files.

openseq2seq icon openseq2seq

Distributed (muti-gpu and multi-node) sequence to sequence learning

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