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所在平台: Udemy |
课程主页: https://www.udemy.com/course/complete-machine-learning-data-science-with-r-programming/
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课程名称：机器学习、商业分析与R编程与Python 课程概述： 本课程将全面讲授机器学习、深度学习、商业分析和数据科学，使用R和Python语言，覆盖应用统计、数据可视化及多个机器学习模型，包括主成分分析（PCA）、神经网络、分类与回归树（CART）和逻辑回归等。学员将使用真实数据构建模型，并学习如何处理机器学习和深度学习项目，例如图像识别。课程包括大量项目、代码文件和作业，采用R和Python进行教学。 更新内容包括： - 深度学习基础及其在图像识别中的应用，使用Keras构建多层感知机模型。 - Python机器学习和数据科学的基础介绍，包括Anaconda分发、Jupyter Notebook、Numpy、Pandas等工具的使用。 - 数据分析与可视化，包括使用Matplotlib和Seaborn进行数据可视化。 - 逻辑回归和线性回归等模型的详细讲解，确保对基础知识的巩固。 这个课程与其他机器学习课程的不同之处在于其全面性，除了常见的机器学习技术外，还包括ANOVA和CART等额外技术。课程结构划分为多个部分，涵盖R编程、数据选择与处理、应用统计及数据可视化，帮助学员掌握数据科学和机器学习的框架。 课程亮点： - R语言下的机器学习可视化 - 机器学习的应用统计 - 机器学习基础知识 - 使用R实现ANOVA和机器学习树算法 - KNN、朴素贝叶斯及神经网络等多种技术实施 注册课程后，学员将获得： - 职业指导，帮助进入数据科学领域 - 如何建立个人作品集的指导 - 完成10个以上的项目，丰富个人作品集 - 终身访问课程内容，自主学习进度 这个课程不仅适合希望深入学习机器学习与数据科学的初学者，也适合希望进一步提升技能的中级学习者。
Learn complete Machine learning, Deep learning, business analytics & Data Science with R & Python covering applied statistics, R programming, data visualization & machine learning models like pca, neural network, CART, Logistic regression & more. You will build models using real data and learn how to handle machine learning and deep learning projects like image recognition. You will have lots of projects, code files, assignments and we will use R programming language as well as python. Release notes- 01 MarchDeep learning with Image recognition & KerasFundamentals of deep learningMethodology of deep learningArchitecture of deep learning modelsWhat is activation function & why we need themRelu & Softmax activation functionIntroduction to KerasBuild a Multi-layer perceptron model with Python & Keras for Image recognitionRelease notes- 30 November 2019 Updates;Machine learning & Data science with PythonIntroduction to machine learning with pythonWalk through of anaconda distribution & Jupyter notebookNumpyPandasData analysis with Python & PandasData Visualization with PythonData Visualization with PandasData visualization with MatplotlibData visualization with SeabornMulti class linear regression with PythonLogistic regression with PythonI am avoiding repeating same models with Python but included linear regression & logistic regression for continuation purpose.Going forward, I will cover other techniques with Python like image recognition, sentiment analysis etc.Image recognition is in progress & course will be updated soon with it. Unlike most machine learning courses out there, the Complete Machine Learning & Data Science with R-2019 is comprehensive. We are not only covering popular machine learning techniques but also additional techniques like ANOVA & CART techniques. Course is structured into various parts like R programming, data selection & manipulation, applied statistics & data visualization. This will help you with the structure of data science and machine learning. Here are some highlights of the program: Visualization with R for machine learning Applied statistics for machine learning Machine learning fundamentals ANOVA Implementation with R Linear regression with R Logistic Regression Dimension Reduction Technique Tree-based machine learning techniques KNN Implementation Naïve Bayes Neural network machine learning technique When you sign up for the course, you also: Get career guidance to help you get into data science Learn how to build your portfolio Create over 10 projects to add to your portfolio Carry out the course at your own pace with lifetime access
