字节跳动AI机器学习算法（合规方向）实习生-国际支付
实习兼职A28747A地点：北京状态：招聘
工作描述
任职要求 1、2027届本科及以上学历在读，计算机科学、计算机工程、统计学、应用数学、数据科学或其他相关专业； 2、具备扎实的数据结构与算法基础，熟练掌握LLM/LVM/多模态/GNN/CV/NLP中至少一种算法，精通SFT、DPO、RL等大模型后训练算法原理，具备扎实的机器学习、深度学习理论基础； 3、熟悉TensorFlow/PyTorch/MXNet/Hugging Face Transformers等中至少一种框架，且了解其训练与部署细节； 4、熟练掌握Python、Java、C/C++等至少一种编程语言，具备较强编码能力。 加分项 1、发表过CCF A/B类论文或获得过AI相关竞赛TOP奖项者优先。 工作职责 ByteIn…
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包括英文材料
学历+
数据科学+
https://roadmap.sh/ai-data-scientist
Step by step roadmap guide to becoming an AI and Data Scientist
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
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/
大模型+
https://www.youtube.com/watch?v=xZDB1naRUlk
You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers.
https://www.youtube.com/watch?v=zjkBMFhNj_g
LVM+
https://www.lightly.ai/blog/large-vision-models
Large Vision Models (LVMs) are transforming computer vision by using Transformer-based architectures to analyze images like language.
https://www.phdata.io/blog/what-are-large-vision-models-and-how-do-they-work/
Large Vision Models (LVMs) have transformed the field of computer vision, setting new benchmarks in image recognition, image segmentation, and object detection.
https://www.youtube.com/watch?v=lirjgIgngUE
GNN+
https://distill.pub/2021/gnn-intro/
Neural networks have been adapted to leverage the structure and properties of graphs.
https://gnn.seas.upenn.edu/
Graph Neural Networks (GNNs) are information processing architectures for signals supported on graphs.
https://www.ibm.com/think/topics/graph-neural-network
Graph neural networks (GNNs) are a deep neural network architecture that is popular both in practical applications and cutting-edge machine learning research.
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.
SFT+
https://cameronrwolfe.substack.com/p/understanding-and-using-supervised
Understanding how SFT works from the idea to a working implementation...
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