字节跳动多模态算法实习生-抖音直播
实习兼职A120693地点:北京状态:招聘
任职要求
1、本科及以上学历在读,人工智能、计算机、模式识别等相关专业优先; 2、有NLP、CV、数据处理等相关优质论文发表、比赛获奖或项目经验; 3、具有优秀的编程基础,熟练使用Python/C++等至少一种编程语言,熟练使用TensorFlow/PyTorch等至少一种深度学习框架; 4、熟悉Attention、Transformer、BERT、GPT等常用模型结构,熟悉LLaMA、ChatGLM等开源大模型原理与实现,有开源模型调优训练经验者优先; 5、优秀的分析和解决问题的能力,对解决具有挑战性的问题充满激情,良好的沟通和团队合作能力。
工作职责
日常实习:面向全体在校生,为符合岗位要求的同学提供为期3个月及以上的项目实践机会。 团队介绍:直播团队负责为抖音集团提供直播服务。团队负责直播平台技术和直播业务研发,打造灵活稳定的直播服务平台,为用户提优质直播体验,支持电商、本地生活、游戏、节目、多人互动等不同类型的业务场景。直播业务发展迅猛,处于行业头部地位,业务发展空间巨大。现在加入我们,和优秀的人一起做有挑战的事,你的技术与创意将影响亿级用户,激发创意和丰富生活。 1、参与抖音直播助手项目建设,面向主播开播的全流程,打造全方位、自迭代的智能直播专家,探索直播领域垂类大模型的建设工作; 2、参与研发提效助手项目建设,打造面向软件研发全生命周期的提效助手,完成研发知识资产的建设和模型内化; 3、参与新业务的探索研究,结合对业务场景的充分理解,寻找最佳解决方案。
包括英文材料
学历+
模式识别+
https://www.mathworks.com/discovery/pattern-recognition.html
Pattern recognition is the process of classifying input data into objects, classes, or categories using computer algorithms based on key features or regularities.
https://www.microsoft.com/en-us/research/wp-content/uploads/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf
Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science.
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.
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.
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
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.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
Transformer+
https://huggingface.co/learn/llm-course/en/chapter1/4
Breaking down how Large Language Models work, visualizing how data flows through.
https://poloclub.github.io/transformer-explainer/
An interactive visualization tool showing you how transformer models work in large language models (LLM) like GPT.
https://www.youtube.com/watch?v=wjZofJX0v4M
Breaking down how Large Language Models work, visualizing how data flows through.
BERT+
https://www.youtube.com/watch?v=xI0HHN5XKDo
Understand the BERT Transformer in and out.
GPT+
https://www.youtube.com/watch?v=kCc8FmEb1nY
We build a Generatively Pretrained Transformer (GPT), following the paper "Attention is All You Need" and OpenAI's GPT-2 / GPT-3.
ChatGLM+
https://www.youtube.com/watch?v=EXUX0MjBzI0
In this step-by-step tutorial, you'll learn how to use ChatGLM, one of the most powerful and completely free AI video generators available today.
https://www.youtube.com/watch?v=fGpXj4bl5LI
Exploring the concept of a GLM (General Language Model) and working with ChatGLM6B.
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
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