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lstm_attention_tf

Add attention layer to LSTM/word2vec model for sentiment analysis using tensorflow

lstm_chatbot

Implementation of a Deep Learning chatbot using Keras with Tensorflow backend

lstm_fault_detection

lstm_han

LSTM and Hierarchical Attention Network on DSVM

lstm_learn

a implement of LSTM using Keras for time series prediction regression problem

lstm_stock_prediction

This is an LSTM stock prediction using Tensorflow with Keras on top.

lstm_tensorflow

An LSTM network solution for MAL recommendations.

lstm_tsc

An LSTM for time-series classification

lsun

LSUN Dataset Documentation and Demo Code

lsuv-keras

Simple implementation of the LSUV initialization in keras

lucid

luigi

Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.

lulu

[Unmaintained] A simple and clean video/music/image downloader 👾

luminoth

Deep Learning toolkit for Computer Vision

luna16_multi_size_3dcnn

An implement of paper "Multi-level Contextual 3D CNNs for False Positive Reduction in Pulmonary Nodule Detection"

lung-segmentation-2d

Lung fields segmentation on CXR images using convolutional neural networks.

lv_groundhog

lynda-video-downloader

This Lynda.com Video Downloader written with Python 3 will help you download all specified course videos in separate folders. You need to be an existing Lynda.com user in order to use it.

m4-methods

Includes the source code of the methods which participated in the M4 Competition

maaf

Modality-Agnostic Attention Fusion for visual search with text feedback

mabfdr

Code for the MAB-FDR framework introduced in "A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control", NIPS 2017

mac-network

Implementation for the paper "Compositional Attention Networks for Machine Reasoning" (Hudson and Manning, ICLR 2018)

mach

Extreme Classification in Log Memory via Count-Min Sketch

machine-comprehension

MACHINE READING COMPREHENSION WITH SELF-MATCHING NETWORKS

machine-learning

Content for Udacity's Machine Learning curriculum

machine-learning-1

Implemented Naïve Bayes, Support Vector Machines, Random Forests to classify faces and documents and achieved 92% average accuracy using R and Python. Implemented EM algorithms to segment images in Python. Used TensorFlow framework to implement Convolution Neural Networks to recognize hand written digits from MNIST datasets and images from famous Cifar 10 datasets.

machine-learning-a-probabilistic-perspective-solutions

My solutions to Kevin Murphy Machine Learning Book

machine-learning-algorithms

Code repository for Machine Learning Algorithms, published by Packt

machine-learning-and-pattern-recognition

Implementation of Machine Learning Algorithms

machine-learning-cheat-sheet

Classical equations and diagrams in machine learning