知乎推荐算法专家
社招全职5年以上地点:北京状态:招聘
任职要求
1、有用户行为序列建模经验优先; 2、本科及以上学历,5年及以上互联网工作经验,有个性化推荐、广告、自然语言处理、机器学习等项目实践经验; 3、深入理解机器学习算法,熟练使用至少一种深度学习开源框架,如tensorflow、pytorch, paddlepaddle 等; 4、熟悉常用数据结构,具备扎实的算法基本功,热爱编程,熟悉Python , go,c++或其他主流编程语言; 5、具有较强的沟通表达能力,善于学习,能迅速理解产品需求,关注用户体验; 6、有较强的责任心和事业心,有严密的逻辑思维,有追求卓越的精神,能够自我驱动。
工作职责
1、参与亿级规模的推荐算法优化,负责个性化推荐算法研发; 2、通过图模型、向量召回、深度学习、迁移学习、多目标排序模型等,提升用户体验以及内容分发效率; 3、通过内容理解、用户理解、用户长短期兴趣建模,提升推荐的精准性; 4、深入产品和业务,从数据中发现机制和算法的不足,提出改进方案并推动落地; 5、和团队一起攻克算法落地中的高性能、高并发、可用性等各种技术难题; 6、跟踪前沿推荐算法技术,结合业务特点做算法改进和技术创新。
包括英文材料
学历+
NLP+
https://www.youtube.com/watch?v=fNxaJsNG3-s&list=PLQY2H8rRoyvzDbLUZkbudP-MFQZwNmU4S
Welcome to Zero to Hero for Natural Language Processing using TensorFlow!
https://www.youtube.com/watch?v=R-AG4-qZs1A&list=PLeo1K3hjS3uuvuAXhYjV2lMEShq2UYSwX
Natural Language Processing tutorial for beginners series in Python.
https://www.youtube.com/watch?v=rmVRLeJRkl4&list=PLoROMvodv4rMFqRtEuo6SGjY4XbRIVRd4
The foundations of the effective modern methods for deep learning applied to NLP.
机器学习+
https://www.youtube.com/watch?v=0oyDqO8PjIg
Learn about machine learning and AI with this comprehensive 11-hour course from @LunarTech_ai.
https://www.youtube.com/watch?v=i_LwzRVP7bg
Learn Machine Learning in a way that is accessible to absolute beginners.
https://www.youtube.com/watch?v=NWONeJKn6kc
Learn the theory and practical application of machine learning concepts in this comprehensive course for beginners.
https://www.youtube.com/watch?v=PcbuKRNtCUc
Learn about all the most important concepts and terms related to machine learning and AI.
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
TensorFlow+
https://www.youtube.com/watch?v=tpCFfeUEGs8
Ready to learn the fundamentals of TensorFlow and deep learning with Python? Well, you’ve come to the right place.
https://www.youtube.com/watch?v=ZUKz4125WNI
This part continues right where part one left off so get that Google Colab window open and get ready to write plenty more TensorFlow code.
PyTorch+
https://datawhalechina.github.io/thorough-pytorch/
PyTorch是利用深度学习进行数据科学研究的重要工具,在灵活性、可读性和性能上都具备相当的优势,近年来已成为学术界实现深度学习算法最常用的框架。
https://www.youtube.com/watch?v=V_xro1bcAuA
Learn PyTorch for deep learning in this comprehensive course for beginners. PyTorch is a machine learning framework written in Python.
PaddlePaddle+
https://learnopencv.com/paddlepaddle/
PaddlePaddle (PArallel Distributed Deep LEarning) is an open-source deep learning framework released by Baidu in 2016.
https://www.paddlepaddle.org.cn/tutorials
本课程采用飞桨特色的「横纵式」 教学法,从易到难,学习难度逐层递进,并结合图形和案例进行讲解,力求让刚接触深度学习的读者可以快速理解。
数据结构+
https://www.youtube.com/watch?v=8hly31xKli0
In this course you will learn about algorithms and data structures, two of the fundamental topics in computer science.
https://www.youtube.com/watch?v=B31LgI4Y4DQ
Learn about data structures in this comprehensive course. We will be implementing these data structures in C or C++.
https://www.youtube.com/watch?v=CBYHwZcbD-s
Data Structures and Algorithms full course tutorial java
Python+
https://liaoxuefeng.com/books/python/introduction/index.html
中文,免费,零起点,完整示例,基于最新的Python 3版本。
https://www.learnpython.org/
a free interactive Python tutorial for people who want to learn Python, fast.
https://www.youtube.com/watch?v=K5KVEU3aaeQ
Master Python from scratch 🚀 No fluff—just clear, practical coding skills to kickstart your journey!
https://www.youtube.com/watch?v=rfscVS0vtbw
This course will give you a full introduction into all of the core concepts in python.
Go+
https://www.youtube.com/watch?v=8uiZC0l4Ajw
学习Golang的完整教程!从开始到结束不到一个小时,包括如何在Go中构建API的完整演示。没有多余的内容,只有你需要知道的知识。
C+++
https://www.learncpp.com/
LearnCpp.com is a free website devoted to teaching you how to program in modern C++.
https://www.youtube.com/watch?v=ZzaPdXTrSb8
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1.参与公司个性化推荐算法、用户增长等,优化人货场的匹配; 2.通过表征学习、图模型、迁移学习、多任务学习等技术提升信息匹配的效率,让每个用户可以便捷的找到优质好货; 3.挖掘和分析海量用户行为数据,进行用户长短期兴趣建模,以及潜在兴趣预测,提升推荐的精准性; 4.结合OTA的业务特性,进行模型和算法创新,打造业界领先的推荐算法和系统。
更新于 2024-07-19