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所在平台: Udemy |
课程主页: https://www.udemy.com/course/beginner-guide-to-artificial-intelligence-machine-learning/
课程评论：没有评论
课程名称：初学者人工智能与机器学习指南 课程概述： 本课程旨在帮助学生掌握机器学习的基本知识和技能。学员将学习如何实现机器学习算法，提升模型性能，并建立个人作品集以增强简历吸引力。内容涵盖监督学习和非监督学习，利用数据可视化工具（如Matplotlib）探索大数据集。学员将学习NumPy在机器学习中的应用，以及如何在项目中使用流行的库Scikit-learn。课程内容包括分类与回归建模，掌握机器学习的应用，并根据问题类型选择合适的模型。 此外，学员将了解数据科学工作流程最佳实践，学习使用最新版本的Python 3编程，数据预处理、清洗和分析等技能。课程将指导学员搭建数据科学与机器学习的开发环境，并提供完整的代码和笔记，以帮助学员建立数据科学与机器学习项目的作品集，为未来的职业发展做好准备。 通过真实案例研究，学员将能够了解行业中的实际操作。同时，课程将针对学员的背景提供职业发展指导，帮助其在接下来的六个月内规划职业路径。学员将全面掌握神经元、感知器、多层感知器和变换器等基础概念，并对卷积神经网络和递归神经网络有良好的认识。
Implement Machine Learning algorithmsHow to improve your Machine Learning ModelsBuild a portfolio of work to have on your resumeSupervised and Unsupervised LearningExplore large datasets using data visualization tools like Matplotlib Learn NumPy and how it is used in Machine LearningLearn to use the popular library Scikit-learn in your projectsLearn to perform Classification and Regression modellingMaster Machine Learning and use it on the jobLearn which Machine Learning model to choose for each type of problemLearn best practices when it comes to Data Science WorkflowLearn how to program in Python using the latest Python 3Learn to pre process data, clean data, and analyze large data.Developer Environment setup for Data Science and Machine LearningA portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks providedReal life case studies and projects to understand how things are done in the real worldGuidance to choose your career path based on your background and build the path in next 6 monthsComprehensive understanding on foundational concepts like Neurons, Perceptron, Multilayer Perceptron, Transformers. Good overview on Convolution Neural Networks and Recurrent Neural Networks
