{"m1":["resume_head","resume_name","resume_base_info"],"m2":[],"m3":["resume_job","resume_edu","resume_work","resume_hobby","resume_skill","resume_honor","resume_summary","resume_internship","resume_project","resume_portfolio","cbae7459-31b4-4f7f-be21-83a67aea712c","34dd907e-4c69-4d44-94db-98b0d5831759"],"m4":[]}
.resume_main[data_color] .skill_item .skill_slider span::before{background-color:${color};}
.resume_main[data_color] .skill_slider s i{background-color:${relative_skill_color};}
.resume_main[data_color] .skill_style_01.skill_item .skill_slider s {border-color:${relative_skill_color};}
.resume_main[data_color] .skill_style_01.skill_item .skill_slider s i{background-color:${relative_skill_color};}
.resume_main[data_color] .skill_style_04.skill_item .skill_slider[data_level="average"] i,.resume_main[data_color] .skill_style_07.skill_item .skill_slider[data_level="average"] i{box-shadow:24px 0 0 ${relative_skill_color}, 48px 0 0 #ccc, 72px 0 0 #ccc, 96px 0 0 #ccc, 120px 0 0 #ccc;}
.resume_main[data_color] .skill_style_04.skill_item .skill_slider[data_level="good"] i,.resume_main[data_color] .skill_style_07.skill_item .skill_slider[data_level="good"] i{box-shadow:24px 0 0 ${relative_skill_color}, 48px 0 0 ${relative_skill_color}, 72px 0 0 #ccc, 96px 0 0 #ccc, 120px 0 0 #ccc;}
.resume_main[data_color] .skill_style_04.skill_item .skill_slider[data_level="advanced"] i,.resume_main[data_color] .skill_style_07.skill_item .skill_slider[data_level="advanced"] i{box-shadow:24px 0 0 ${relative_skill_color}, 48px 0 0 ${relative_skill_color}, 72px 0 0 ${relative_skill_color}, 96px 0 0 #ccc, 120px 0 0 #ccc;}
.resume_main[data_color] .skill_style_04.skill_item .skill_slider[data_level="expert"] i,.resume_main[data_color] .skill_style_07.skill_item .skill_slider[data_level="expert"] i{box-shadow:24px 0 0 ${relative_skill_color}, 48px 0 0 ${relative_skill_color}, 72px 0 0 ${relative_skill_color}, 96px 0 0 ${relative_skill_color}, 120px 0 0 #ccc;}
.resume_main[data_color] .skill_style_08.skill_item .skill_slider[data_level="average"] i{box-shadow:9px 0 0 ${relative_skill_color}, 18px 0 0 ${relative_skill_color}, 27px 0 0 ${relative_skill_color}, 36px 0 0 ${relative_skill_color}, 45px 0 0 ${relative_skill_color},54px 0 0 #ccc,63px 0 0 #ccc,72px 0 0 #ccc,81px 0 0 #ccc;}
.resume_main[data_color] .skill_style_08.skill_item .skill_slider[data_level="good"] i{box-shadow:9px 0 0 ${relative_skill_color}, 18px 0 0 ${relative_skill_color}, 27px 0 0 ${relative_skill_color}, 36px 0 0 ${relative_skill_color}, 45px 0 0 ${relative_skill_color},54px 0 0 ${relative_skill_color},63px 0 0 #ccc,72px 0 0 #ccc,81px 0 0 #ccc;}
.resume_main[data_color] .skill_style_08.skill_item .skill_slider[data_level="advanced"] i{box-shadow:9px 0 0 ${relative_skill_color}, 18px 0 0 ${relative_skill_color}, 27px 0 0 ${relative_skill_color}, 36px 0 0 ${relative_skill_color}, 45px 0 0 ${relative_skill_color},54px 0 0 ${relative_skill_color},63px 0 0 ${relative_skill_color},72px 0 0 #ccc,81px 0 0 #ccc;}
.resume_main[data_color] .skill_style_08.skill_item .skill_slider[data_level="expert"] i{box-shadow:9px 0 0 ${relative_skill_color}, 18px 0 0 ${relative_skill_color}, 27px 0 0 ${relative_skill_color}, 36px 0 0 ${relative_skill_color}, 45px 0 0 ${relative_skill_color},54px 0 0 ${relative_skill_color},63px 0 0 ${relative_skill_color},72px 0 0 ${relative_skill_color},81px 0 0 #ccc;}
.resume_main[data_color] .hobby_item .hobby_item_con .hobby_item_list a.alifont{border-color:${relative_hobby_color};color:${relative_hobby_color}; }
/* ������ */
.resume_main[data_color] .resume_cover .cover_html svg [data-svg="fill"] {fill:${color};}
.resume_main[data_color] .resume_cover .cover_html svg [data-svg="stroke"] {stroke:${color};}
.resume_main[data_color] .resume_letter .letter_html svg [data-svg="fill"] {fill:${color};}
.resume_main[data_color] .resume_letter .letter_html svg [data-svg="stroke"] {stroke:${color};}
.resume_main[data_color] .resume_letter .letter_html svg [data-fill="fill"] {fill:${color};}
.resume_main[data_color] .resume_cover[data-type="07"] .resume_cover_avatar{border-color: ${color};}
.resume_main[data_color] .resume_cover[data-type="07"] .resume_cover_content{background:${color}}
.resume_main[data_color] .resume_cover[data-type="07"] .cover_item_list a.alifont{color: ${color};}
.resume_main[data_color] .resume_cover[data-type="08"] .resume_cover_content::after{background:${color}}
.resume_main[data_color] .resume_cover[data-type="09"] .resume_cover_content{background:${color}}
.resume_main[data_color] .resume_cover[data-type="09"] .cover_item_list a.alifont{color: ${color};}
.resume_main[data_color] .resume_cover[data-type="10"]{background-color:${color}}
.resume_main[data_color] .resume_cover[data-type="11"] .resume_cover_content{background-color:${color}}
.resume_main[data_color] .resume_cover[data-type="14"]{background-color:${color}}
.resume_main[data_color] .resume_cover[data-type="15"]{background-color:${color}}
.resume_main[data_color] .resume_cover[data-type="19"] .resume_cover_word::before{background-color:${color}}
.resume_main[data_color] .resume_cover[data-type="20"]{background-color:${color}}
.resume_main[data_color] .resume_letter[data-type="06"]{background-color:${color}}
.resume_main[data_color] .resume_letter[data-type="12"]{background-color:${color}}
.resume_main[data_color] .resume_item dl dt span.resume_item_title_span,.resume_main[data_color] .name_item .name-con .name{color:${color};}
.resume_main[data_color] .resume_item dl dt{border-bottom-color:${color};}
.resume_main[data_color] .resume_item dl dt span.resume_item_title_span{color:${color};}
-
姓名
-
锤子简历
世界属于那些勤于思考的人,更属于那些善于行动的人。
-
教育背景
-
2011.09-2015.06
锤子简历大学
软件工程
-
工作经验
-
2019.01-2019.11
锤子简历公司
资深推荐算法工程师
- 参与汽车之家智能营销项目,负责其中人工干预模块;
- 负责实现智能营销广告投放用户行为数据的自动反馈,以帮助持续提升算法 CTR;
- 负责APP 用户画像的优化,行为分析,为排序模型提供特征支持;
- 负责以用户为单位,基于行为对其分群,分析页面浏览情况;
- 负责以页面为单位,基于图论模型分析不同页面之间的跳转情况;
2016.01-2018.12
锤子简历公司
资深推荐算法工程师
- 负责推荐算法架构的设计,领导推荐算法团队;
- 负责个性化推荐方向的策略,用户画像,用户标签体系的建立,以及推荐系统的效果改进;
- 负责应用数据挖掘,机器学习、深度学习等技术,为用户提供推荐和排序,提升个性化推荐的效果,改进用户体验;
-
自我评价
-
之前一直从事硬件方面的工作,现在想从事人工智能深度学习方面的工作。在最近的半年时间里,自学了python、Tensorflow、CNN/RNN、ubuntu等大数据人工智能方面的知识。我深知在换行业和职业这种折腾的过程中会遇到很多困难,但我依然走上了这条道路,因为折腾在抵抗麻木的过程中,会让生活变得更有意思。希望各位HR能给个面试机会。
-
作品展示
-
+(支持jpg/png格式,单张图片不超过2M,最多支持添加8张图片)
-
其他
-
- 技能: 掌握 CNN、RNN、LSTM 等基本神经网络结构,熟练图像识别、分类和目标检测,熟练深度学习图像算法;熟悉 NLP,使用过自然语言处理方法中的文本情感分析、对话机器人、意图分析等;了解语音识别及其 CTC 等;了解 DNN 以及 CB、 CF、 GBDT 、 TF-IDF、 LR 等推荐系统常用算法。 掌握Python 、Java 的基本运用;熟练 Tensorflow,掌握 numpy、matplotlib 的基本使用;了解pytorch、Scikit-neuralnetwork、Scikit-learn、pandas 等函数包的使用;熟悉 DenseNet、ResNet、GoogleNet 等深度学习框架,掌握 Bert、attention、transformer 等新型热门自然语言处理技术,具备良好的数学基础和英语阅读能力;掌握最新人工智能框架常用的激活函数:ReLU、Tanh、sigmoid 等;熟练神经网络,且了解 SVM、KNN、决策树、随机森林、逻辑回归、Nave Bayes、EM、k-means、Adaboost 等传统机器学习算法以及常见数据分析方法;了解Q-learning、 Sarsa、 DQN、 Double DQN、 Policy Gradient、Actor Critic(DDPG、A3C、DDPO)等算法;了解分布式集群 HDFS、 MapReduce 及其生态圈组件(Hbase、 Hive 等)、Shell、ELK、微服务、SaaS 应用等;
-
项目经历
-
- 宠乐园是一款爱宠人群综合类社交平台,它包括:主题发布、趣味互动、社交圈粉、新型探索、萌系可爱等板块,该软件致力于给用户带来更好的用户使用体验,主要包括创建ALS 模型,召回商品,神经网络实现 CTR 预估,离线数据处理,实时推荐等等;
- 使用 flume 收集用户日志,将用户行为采集到 HDFS,使用用户基本信息训练 K-Means聚类,解决用户冷启动问题,Spark streaming 实时处理 kafka 发送过来的点击日志,实时更新特征,实时更新召回集,使用 tfidf、textrank 提取物品关键词、主题词,使用 word2vec处理文本内容,构建物品画像;
- 使用用户基本信息和用户的行为信息对用户标签化即构建用户画像,标签权重随时间指数衰减;解析用户行为日志,实时增加物品的点击次数等信息,将热门物品存入到 kafka中,查询 redis 中是否也有也存在此热门物品;