小米算法实习生
实习兼职地点:北京状态:招聘
任职要求
1. 计算机科学、自动化、电子工程、机械工程、人工智能、模式识别等相关专业,硕士及以上学历; 2. 熟练掌握至少一门编程语言,优先Python,熟悉C++/Java者优先,掌握OpenCV、PyTorch/TensorFlow等机器视觉/深度学习框架; 3. 具备机器视觉基础,了解图像预处理、特征…
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工作职责
1. 辅助完成机器视觉技术在汽车智能制造场景的落地,包括产线视觉检测、零部件识别与定位、工艺参数视觉监控等项目的算法设计与调试; 2. 参与汽车工厂智能制造相关项目预研与实施,聚焦现场生产参数动态调优,如设备运行参数、工艺参数的实时分析与优化算法开发,提升产线效率与产品良率; 3. 对接产线实际业务需求,收集并处理生产数据,通过机器学习、深度学习等方法构建参数调优模型,持续迭代优化算法并验证效果; 4. 配合团队完成算法原型开发、测试与部署,撰写技术文档并跟进项目落地后的效果反馈。
包括英文材料
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.
学历+
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
Java+
https://www.youtube.com/watch?v=eIrMbAQSU34
Master Java – a must-have language for software development, Android apps, and more! ☕️ This beginner-friendly course takes you from basics to real coding skills.
OpenCV+
https://learnopencv.com/getting-started-with-opencv/
At LearnOpenCV we are on a mission to educate the global workforce in computer vision and AI.
https://opencv.org/university/free-opencv-course/
This free OpenCV course will teach you how to manipulate images and videos, and detect objects and faces, among other exciting topics in just about 3 hours.
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