Pinned Repositories
ape-x
This repo replicates the results Horgan et al obtained in "Distributed Prioritized Experience Replay"
baselines
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
bbox_utils
bq_job_viewer
caffe_template
DDPG_Eager
DecalCaster
DSEBM
gpu_docker
teflon
laket's Repositories
laket/DSEBM
laket/DDPG_Eager
laket/DecalCaster
laket/gpu_docker
laket/teflon
laket/ape-x
This repo replicates the results Horgan et al obtained in "Distributed Prioritized Experience Replay"
laket/baselines
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
laket/bbox_utils
laket/bq_job_viewer
laket/caffe_template
laket/caltech-pedestrian-dataset-converter
Download Caltech Pedestrian Dataset and convert them for Python users without using MATLAB
laket/chef_environment
chef repository to create my standard development environment for Ubuntu.
laket/coco_classification
laket/colorize
laket/deconv_cifar10
laket/deep-visualization-toolbox
laket/EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
laket/general_grad_sample
laket/golearn
laket/gomoku
gomokunarabe board library
laket/ladder_test
laket/qiita_adobe_stat
laket/StringImageMaker
laket/tensorflow
Computation using data flow graphs for scalable machine learning
laket/tensorflow_unaggregated