Pinned Repositories
2019Advanced-course-project
2019 Advanced course on digital (hardware) technology using re:rulo ( autonomous robotic vacuum cleaner) equiped with Jetson TX2, Rider, Intel RealSence and so on
2019UNIRITA_MLOps_research
Research and develop MLOPs-oriented frameworks, which accelerate data analysis processing and buidling AI system with pipeline management tool and extended functions
CollaborativeVAE
Jaist_AWS
Introduction to how to use AWS through JAIST CLOUD
mxnet-for-cdl
Collaborative Deep Learning for Recommender Systems.
PACE2017
A step-by-step Keras implementation of PACE (Preference And Context Embedding) described in our KDD 2017 paper.
RytTnk.github.io
My web site
Surprise
A Python scikit for building and analyzing recommender systems
Survey
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners with Latest APIs
RytTnk's Repositories
RytTnk/2019Advanced-course-project
2019 Advanced course on digital (hardware) technology using re:rulo ( autonomous robotic vacuum cleaner) equiped with Jetson TX2, Rider, Intel RealSence and so on
RytTnk/CollaborativeVAE
RytTnk/PACE2017
A step-by-step Keras implementation of PACE (Preference And Context Embedding) described in our KDD 2017 paper.
RytTnk/TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners with Latest APIs
RytTnk/2019UNIRITA_MLOps_research
Research and develop MLOPs-oriented frameworks, which accelerate data analysis processing and buidling AI system with pipeline management tool and extended functions
RytTnk/Jaist_AWS
Introduction to how to use AWS through JAIST CLOUD
RytTnk/RytTnk.github.io
My web site
RytTnk/Surprise
A Python scikit for building and analyzing recommender systems
RytTnk/Survey
RytTnk/Autoencoders_cf
RytTnk/Autorec
Autorec (Autoencoders Meet Collaborative Filtering)
RytTnk/baby-steps-of-rl-ja
Pythonで学ぶ強化学習 -入門から実践まで- サンプルコード
RytTnk/BayesianOptimization
A Python implementation of global optimization with gaussian processes.
RytTnk/collaborative-rnn
A TensorFlow implementation of the collaborative RNN (Ko et al, 2016).
RytTnk/DeepFM
Implementation of DeepFM using tensorflow.
RytTnk/entity2rec
entity2rec generates item recommendation from knowledge graphs
RytTnk/GRU4Rec
GRU4Rec is the cleaned & simplified implementation of the algorithm of the "Session-based Recommendations with Recurrent Neural Networks" paper, published at ICLR 2016. The code is stripped of features that we had found to be unhelpful in increasing accuracy.
RytTnk/keras_gpyopt
Using Bayesian Optimization to optimize hyper parameter in Keras-made neural network model.
RytTnk/ML_Template
Template for data analysis and modeling
RytTnk/models
Models built with TensorFlow
RytTnk/neural_collaborative_filtering
Neural Collaborative Filtering
RytTnk/nimfa
Nimfa - A Python module for nonnegative matrix factorization
RytTnk/OpenLearning4DeepRecsys
Some deep learning based recsys for open learning.
RytTnk/PACE
Experiment code for Bridging Collaborative Filtering and Semi-Supervised Learning: A Neural Approach for POI recommendation
RytTnk/pyprobml
Python code for "Machine learning: a probabilistic perspective"
RytTnk/sequence-based-recommendations
RytTnk/Study
2017 My research project on Point-of-Interest with Deep learning
RytTnk/tens
same with tensorflow/models? but how got this
RytTnk/tensorflow
Computation using data flow graphs for scalable machine learning
RytTnk/tensorflow-DeepFM
Tensorflow implementation of DeepFM for CTR prediction.