minghao2016 Goto Github PK

analyze-ab-test-results-1

Udacity Data Analyst Nanodegree Project4 Analyze-AB-Test-Results

analyze_marketing_data-using-pyspark

Your client―a Portuguese banking institution—ran a marketing campaign to convince potential customers to invest in bank term deposit. Information related to direct marketing campaigns of the bank are as follows. The marketing campaigns were based on phone calls. Often, the same customer was contacted more than once through phone, in order to assess if they would want to subscribe to the bank term deposit or not.

anchor-baggage

Experimentation code for the article "Building Topic Models Based on Anchor Words" based on the paper "Learning Topic Models: Going beyond SVD" by Sanjeev Arora, Rong Ge, and Ankur Moitra.

anchor-graph

anchor-graph-hashing

anchor-regression

andromeda

AsynchroNous Disk-based Representation of MassivE DAta: An R package aimed at replacing ff for storing large data objects.

angel

A Flexible and Powerful Parameter Server for large-scale machine learning

anime-recommender-system

Anime Recommender System project for EECS 445

anintroductiontodeeplearning

Code and accompanying data used in my book "An Introduction to Deep Learning"

ann2

Artificial Neural Networks package for R

annetgpgpu

A GPU (CUDA) based Artificial Neural Network library

annoprobe

annoy

Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

anonlink

Python implementation of anonymous linkage using cryptographic linkage keys

anticlust

Subset partitioning via anticlustering

anvio

An analysis and visualization platform for 'omics data

ao

Alternating optimization of (high-dimensional) functions.

aomisc

Utilities for stat courses

apbs-pdb2pqr

APBS and PDB2PQR software

apexcharter

:bar_chart: R Htmlwidget for ApexCharts.js

applied-statistics

Reference materials of "Probability & Statistics" IPE 205 course

approximate-infinite-dimensional-rcovds

apps-ambit

Applications using AMBIT and examples how to call AMBIT modules

apricot

apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly. See the documentation page: https://apricot-select.readthedocs.io/en/latest/index.html

ar-pred_source

Source code for AR-Pred

arborist

Modular, extensible implementation of the Random Forest (TM) algorithm.

archive

R bindings to libarchive, supporting a large variety of archive formats

arenar

Data generator for Arena - interactive XAI dashboard

arm-workshop-rsc2019

Materials for the rstudio::conf 2019 Advanced R Markdown workshop