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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-data-science-bootcamp-with-r-python/
课程评论：没有评论
课程名称：R和Python机器学习与数据科学训练营 课程概述： 计算与人工智能学院自豪地推出课程“数据工程与Python”。该课程由计算与人工智能学院的专家团队（包括博士、博士候选人、高级讲师、顾问和研究人员）以及行业专家共同设计，旨在帮助学员掌握IT、计算机科学、工程和数据科学领域中2021年最受欢迎的职业技能。课程结束后，学员将能够开启数据挖掘与机器学习的职业生涯。 课程内容包括： 1) 机器学习简介 - 提供全面的A到Z培训与逐步指导 2) 机器学习环境设置 - 逐步指导[R编程与Python] 3) 监督学习 - 包括单变量线性回归、多变量线性回归、逻辑回归、朴素贝叶斯分类器、决策树、支持向量机(SVM)和随机森林 4) 无监督学习 5) 卷积神经网络(CNN) 6) 人工神经网络 7) 实际项目与源代码 课程学习成果： - 熟悉监督与无监督学习的概念，理解数据挖掘与机器学习的必要性。 - 描述智能问题解决方法，通过适当使用机器学习技术。 - 使用最先进的Python框架构建合适的神经网络模型。 - 在R编程与Python中逐步设置机器学习环境。 - 掌握卷积神经网络（CNN）的相关知识。 本课程还提供来自麻省理工学院及其他知名大学的资源，并包含实际项目的源代码。
Academy of Computing & Artificial Intelligence proudly present you the course "Data Engineering with Python". It all started when the expert team of Academy of Computing & Artificial Intelligence (PhD, PhD Candidates, Senior Lecturers , Consultants , Researchers) and Industry Experts. hiring managers were having a discussion on the most highly paid jobs & skills in the IT/Computer Science / Engineering / Data Science sector in 2021. At the end of the Course you will be able to start your career in Data Mining & Machine Learning. 1) Introduction to Machine Learning - [A -Z] Comprehensive Training with Step by step guidance2) Setting up the Environment for Machine Learning - Step by step guidance [R Programming & Python]3) Supervised Learning - (Univariate Linear regression, Multivariate Linear Regression, Logistic regression, Naive Bayes Classifier, Trees, Support Vector Machines (SVM), Random Forest)4) Unsupervised Learning5) Convolutional Neural Networks - CNN6) Artificial Neural Networks 7) Real World Projects with SourceCourse Learning OutcomesTo provide awareness of (Supervised & Unsupervised learning) coming under Machine Learning (Why we need Data Mining & Machine Learning, What is Data Mining, What is Machine Learning, Traditional Programming Vs Machine Learning, Steps to Solve a Data Mining & Machine Learning Problem, Classification , Clustering)Describe intelligent problem-solving methods via appropriate usage of Machine Learning techniques.To build appropriate neural models from using state-of-the-art python framework.To setup the Environment for Machine Learning - Step by step guidance [R Programming & Python]Convolutional Neural Networks - CNNResources from MIT and many famous Universities Projects with Source
