pengyuange Goto Github PK

followers: 3.0 following: 78.0 repos: 381.0 gists: 0.0

Type: User

pengyuange's Projects

bert-vocab-builder

Builds wordpiece(subword) vocabulary compatible for Google Research's BERT

blockchain

Topics evolution and user portrait on blockchain and bitcoin

blockchain-supply-chain-solution

Umbrella repository for blockchain based supply-chain services and clients

bob

Bob is a free signal-processing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, in Switzerland.

botkit

Botkit is an open source developer tool for building chat bots, apps and custom integrations for major messaging platforms.

bounding-box-prediction

bounding box prediction + intention prediction

ccf-bdci-automotive-field-asc-2018

CCF-BDCI 2018年汽车行业用户观点主题及情感识别挑战赛第6名解决方案

char-rnn-tensorflow-1

Multi-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow

chatbot

一个可以自己进行训练的中文聊天机器人，根据自己的语料训练出自己想要的聊天机器人，可以用于智能客服、在线问答、智能聊天等场景。加入seqGAN版本。

chatbot-retrieval

Dual LSTM Encoder for Dialog Response Generation

chatterbot

ChatterBot is a machine learning, conversational dialog engine for creating chat bots

chinese-bert-wwm

Pre-Training with Whole Word Masking for Chinese BERT

chinese-customer-review

Dataset from 'Character-based BiLSTM-CRF Incorporating POS and Dictionaries for Chinese Opinion Target Extraction'

chinese-opinion-target-extraction

Pytorch implementation of "Character-based BiLSTM-CRF Incorporating POS and Dictionaries for Chinese Opinion Target Extraction", ACML2018

chinese_models_for_spacy

SpaCy 中文模型 | Models for SpaCy that support Chinese

chinesecodinginterviewappendix

The source code for the appendix part of the Chinese version of the book Coding Interviews

chinesewordsegmentation

Chinese word segmentation algorithm without corpus（无需语料库的中文分词）

At Mobicom, you are a business analyst and have been urgently called into a meeting with the marketing head and retention manager. The agenda of this meeting is to discuss the results of Industry survey reports that have been just released. In response to these reports, senior management at Mobicom is concerned that the market environment of rising churn rates and declining ARPU will hit them even harder as churn rate at Mobicom is relatively high. Currently they have been focussing on retaining their customers on a reactive basis when the subscriber calls in to close the account. But this alone does not seem to be enough and the management team is keen to take more initiatives on this front. One of these is to roll out targeted proactive retention programs, which include usage enhancing marketing programs to increase minutes of usage (MOU), rate plan migration, and a bundling strategy among others. To be able to effectively drive these retention strategies, a few key questions of interest require urgent attention and you been given the task of showcasing data based insights and recommendations relating to subscriber churn. Churn Market Survey Report Mobile operators who lead in loyalty outperform their competition in network and service quality, as well as in customer care, according to the 2014 Acquisition and Retention Study Report from Nokia. While retention drivers vary by market maturity, delivering excellent quality keeps customers happy and loyal. The study results also show that churn continues to keep operators on their toes with 40% of customers globally planning to switch provider in the next 12 months. Cost and billing plays a key role across markets when deciding to stay with an operator, but is specifically important for emerging markets where 49% of customers consider it to be the most important factor when deciding to stay with an operator, with network and service quality following at 25%. When it comes to data usage, the number of subscribers experiencing problems is high. Among the problems they report are slow download speeds (20%), data throttling (17%) and applications that don’t work (16%). Another key finding of the 2014 Acquisition and Retention Study Report is that recommendations from family and friends have gained in importance in the decision to switch operators. Subscribers who have switched operators in recent months reported two key information sources in their decision: the Internet and recommendation of family and friends. Another report by Ovum forecasts a falling ARPU, which will continue to decline across all markets.

pengyuange Goto Github PK

pengyuange's Projects

Recommend Projects

Recommend Topics

Recommend Org