吴恩达逻辑回归作业matlab

英文回复：
Professor U Nanda is a prominentputer scientist and an authoritative person in the field of machine learning。

He is currently a professor at Stanford University and has served as Vice—President of the Google Data Department。

Professor U Nda is well known for his outstanding contribution in the field of machine and in—depth learning。

Logic regression， an important classification algorithm in the field of machine learning， is widely applied in a number of fields， such as medical diagnosis， risk prediction， advertising rmendations，etc。

Professor U Nda ' s logical regression is important for learners to realize the principles and application of the algorithm model。

The logical regression model is achieved through the use of Matlab programming， which helps learners to better understand the theoretical basis and practical application of the algorithm。

吴恩达教授系著名计算机科学家，机器学习领域的权威人士。

其现任斯坦福大学教职，并曾担任Google大数据部门副总裁。

吴恩达教授以其在机器学习和深度学习领域的杰出贡献而著称。

逻辑回归作为机器学习领域中的一种重要分类算法，被广泛应用于医疗诊断、风险预测、广告推荐等多个领域。

吴恩达教授的逻辑回归作业对于学习者实
现该算法模型的原理和应用具有重要意义。

通过运用Matlab编程实
现逻辑回归模型，有助于学习者更深入地理解该算法的理论基础和实
际应用。

In the logical regression exercise designed by Professor U Nda，students need to program Matlab for training and forecasting
of logical regression models。

First of all， you have to understand the logic of logical regression models and mathematical formulas， such as sigmoid functions and costing functions。

The training and testing data sets are then prepared for processing and profiling。

This is followed by the use of Matlab to write codes to train logical regression model parameters and make predictions。

The performance of the model is assessed and the results summarized are analysed。

By doing this， students not only understand logic regression algorithms in greater depth， but also improve programming and data analysis capabilities。

在吴恩达教授设计的逻辑回归作业里，学生需要用Matlab编程来实
现逻辑回归模型的训练和预测。

首先得搞懂逻辑回归模型的原理和数
学公式，比如sigmoid函数和代价函数的计算方法。

然后准备好训练
数据集和测试数据集，对数据进行处理和特征工程。

接下来就是用Matlab写代码，训练逻辑回归模型的参数和进行预测。

最后要对模型
的表现进行评估，然后分析总结结果。

通过完成这个作业，学生不仅能更深入理解逻辑回归算法，还能提升编程和数据分析能力。

Professor U Nda ' s logical regression is of great learning importance for both beginners in machine learning and practitioners in related fields。

By using Matlab to achieve a logical regression model， learners are able to understand more deeply the rationale and application of logical regression algorithms， while also improving their programming and data analysis capabilities。

Thepletion of logical regression exercises not only helps learners to master the method of realization of machine learning algorithms， but also provides a solid basis for their future research and work in related fields。

吴恩达教授的逻辑回归作业对于机器学习初学者和相关领域的从业者都具有重要的学习意义。

通过运用Matlab实现逻辑回归模型，学习者能够更加深入地理解逻辑回归算法的原理与应用，同时也能够提升其编程能力和数据分析能力。

完成逻辑回归作业不仅有助于学习者掌握机器学习算法的实现方法，还能够为他们未来在相关领域的研究和工作打下稳固的基础。