In the multi-label problem there is no constraint on how many of the classes the instance can be assigned to. Formally, multi-label classification is the problem of finding a model that maps inputs x to binary vectors y (assigning a value of 0 or 1 for each element (label) in y). Problem transformation methods Transformation into binary classification problems binary relevance amounts to independently training one binary classifier for each label.

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Machine Learning Crash Course Courses ML Concepts Introduction to ML First, it gives you a tool to reduce the time you spend programming. Second, it will allow you to customize your products, making them better for specific groups of people. Third, machine learning lets you solve problems that you, as a programmer, have no idea how to do by hand. machine learning changes the way you think about a problem.

Deep Learning with Python PART 1 - FUNDAMENTALS OF DEEP LEARNING 1.What is deep learning? Artificial intelligence, machine learning, and deep learning Before deep learning: a brief history of machine learning Why deep learning? Why now? 2.Before we begin: the mathematical building blocks of neural networks A first look at a neural network Data representations for neural networks tensor: it’s a container for numbers. You may be already familiar with matrices, which are 2D tensors: tensors are a generalization of matrices to an arbitrary number of dimensions (note that in the context of tensors, a dimension is often called an axis).

scikit-learn sklearn preprocessing MultiLabelBinarizer Transforms between iterable of iterables and a multilabel format (binary matrix) utils class_weight compute_class_weight Estimate class weights for unbalanced datasets.

FAQ imbalanced data https://www.tensorflow.org/tutorials/structured_data/imbalanced_data https://stackoverflow.com/questions/43481490/keras-class-weights-class-weight-for-one-hot-encoding https://github.com/jbjorne/TEES/blob/master/Detectors/KerasDetectorBase.py https://towardsdatascience.com/practical-tips-for-class-imbalance-in-binary-classification-6ee29bcdb8a7 https://stackoverflow.com/questions/48485870/multi-label-classification-with-class-weights-in-keras Class weight degrades Multi Label Classification Performance https://datascience.stackexchange.com/questions/28040/class-weight-degrades-multi-label-classification-performance What is the difference between multilabel and multiclass classification? https://www.quora.com/What-is-the-difference-between-multilabel-and-multiclass-classification https://stats.stackexchange.com/questions/260505/should-i-use-a-categorical-cross-entropy-or-binary-cross-entropy-loss-for-binary

Reference https://github.com/AnthonyMRios/multi-label-zero-shot Few-Shot and Zero-Shot Multi-Label Learning for Structured Label Spaces Deep Neural Networks for Multi-Label Text Classification https://github.com/YujiaBao/Distributional-Signatures Induction Networks for Few-Shot Text Classification https://github.com/laohur/LearnToCompareText

Learning Path for Machine Learning Basics of machine learning with TensorFlow Step 1: Understand what ML is all about The book ‘Deep Learning in Python’ by Francois Chollet, creator of Keras, is a great place to get started. Read chapters 1-4 to understand the fundamentals of ML from a programmer’s perspective. Google Developers Machine Learning Crash Course Machine Learning Glossary Step 2: Beyond the basics Take the TensorFlow in Practice Specialization, which takes you beyond the basics into introductory Computer Vision, NLP, and Sequence modelling.

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CS140: Operating Systems and Systems Programming Description 操作系统： 死锁的条件与算法，进程的状态，进程和线程的区别，内存换页算法，同步与互斥等，参考书籍：现代操作系统 Prerequisite Principles of Computer Systems Readings https://web.stanford.edu/~ouster/cgi-bin/cs140-spring20/lectures.php Operating Systems:

CS144: Introduction to Computer Networking Description 计算机网络：OSI模型，三次握手，TCP状态转换图等，参考书籍：计算机网络与UNIX网络编程第一卷 Prerequisites Principles of Computer Systems Readings 《计算机网络：自顶

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CS161: Design and Analysis of Algorithms 算法复杂度分析（Big Oh，Omega，Theta），递归关系和主方法。包括随机算法，分治策略，贪婪算法，hasing，堆，图算