心动ADN 广告算法工程师(上海)
社招全职2年以上技术大类地点:上海状态:招聘
工作描述
任职要求 1. 计算机、数学、统计学或相关专业,具有扎实的机器学习、最优化理论基础; 2.2年以上移动广告变现经验,熟悉联盟广告生态以及具有一定的投放经验者优先; 3. 精通常用的机器学习算法(LR, GBDT, DNN, RL)及深度学习框架(TensorFlow / PyTorch),有实际业务落地经验优先; 4. 精通 Java / C++ / Go 其中至少一种在线开发语言,并熟练使用 Python/SQL 进行数据处理。 工作职责 简介: 1. 我们是谁: 我们搭建了业界领先的广告系统(TapTap 是国内 Top1 的游戏下载和分发平台),正在探索全新的 Agentic 广告平台; 2. 你所共事:不仅有清、…
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包括英文材料
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/
GBDT+
https://developers.google.com/machine-learning/decision-forests/intro-to-gbdt
Like bagging and boosting, gradient boosting is a methodology applied on top of another machine learning algorithm.
https://scikit-learn.org/stable/modules/ensemble.html
Ensemble methods combine the predictions of several base estimators built with a given learning algorithm in order to improve generalizability / robustness over a single estimator.
深度神经网络+
https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi
Learn the basics of neural networks and backpropagation, one of the most important algorithms for the modern world.
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.
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