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所在平台: Udemy |
课程主页: https://www.udemy.com/course/master-machine-learning-and-data-science-with-python/
课程评论：没有评论
课程名称：掌握机器学习和数据科学的Python 课程概述： 欢迎参加全球最优秀的机器学习和数据科学Python课程！准备好开始你的数据科学家之旅了吗？在这个全面的课程中，你将从Python的安装和基础知识开始学习。当你准备就绪后，机器学习介绍部分将为你提供机器学习的全面概述，涵盖所有重要细节，直至你掌握第一个算法。课程将涵盖多种监督和无监督学习算法，从线性回归到知名的提升算法。你还将学习如何使用自然语言处理进行文本分类，解决一个有趣的问题。 数据科学被认为是全球最佳职业之一，正处于蓬勃发展之中。它不仅具有良好的收入潜力，还能让你与全球顶尖公司合作。数据科学家有机会处理有趣的问题，为组织提供价值，并享受改变企业决策方式的成就感。机器学习和数据科学是全球增长最快、需求最旺盛的技能之一，而这种需求正在快速增长。此外，Python是目前最容易学习和使用的编程语言，也是机器学习的首选语言。因此，现在是学习使用Python进行机器学习的最佳时机。 本课程针对初学者和具备一定编程经验的人群设计。无论你来自金融、市场营销、工程、医学，还是刚入行，只要你有学习的热情，这门课程都将是你成为数据科学家的第一步。 该课程包含20小时的高质量视频内容，超过90个高清讲座，每个视频时长在5到20分钟不等。课程中设置了测验，以在每个主题后测试你的知识，确保你在掌握完整知识后再离开章节。此外，课程还提供了许多练习和解决方案，以帮助你实际运用所学知识，所有的练习笔记、解决方案笔记和数据文件均包含在资源文件夹中。 选择这门课程的理由： - 我涵盖了所有重要的机器学习概念，并且在理论与实践中给予了均衡的重视，这是很多其他课程所忽略的。 - 使用图形工具和最佳动画来解释概念，提升学习体验。 - 专门的部分讲解了解决机器学习问题时面临的实际问题，这是其他课程往往缺乏的。 - 将课程价格设置为最低，使每个人都能负担得起。 课程学习的主要内容包括： - 安装Python并设置虚拟环境 - 学习Python编程基础，如变量、列表、元组、集合、字典、条件语句、循环、自定义函数等 - 使用Python进行数据科学和机器学习 - 深入学习所有机器学习模型的理论 - 数据预处理、构建和评估机器学习模型性能 - 实现多种机器学习算法 - 学习可视化技术，例如Matplotlib和Seaborn - 使用SciKit-Learn进行机器学习任务，包括但不限于K-Means聚类、DBSCAN聚类、K-近邻、逻辑回归、线性回归、正则化技术（Lasso和Ridge）、随机森林、决策树、朴素贝叶斯分类器、支持向量机、主成分分析（PCA）、提升技术（Adaboost、Gradient Boost、XGBoost、Catboost和LightGBM）及自然语言处理。 - 处理机器学习问题时的实际问题。 欢迎加入我们，开始你成为数据科学家的旅程！
Welcome to the best Machine Learning and Data Science with Python course in the planet. Are you ready to start your journey to becoming a Data Scientist?In this comprehensive course, you'll begin your journey with installation and learning the basics of Python. Once you are ready, the introduction to Machine Learning section will give you an overview of what Machine Learning is all about, covering all the nitty gritty details before landing on your very first algorithm. You'll learn a variety of supervised and unsupervised machine learning algorithms, ranging from linear regression to the famous boosting algorithms. You'll also learn text classification using Natural Language processing where you'll deal with an interesting problem.Data science has been recognized as one of the best jobs in the world and it's on fire right now. Not only it has a very good earning potential, but also it facilitates the freedom to work with top companies globally. Data scientists also gets the opportunity to deal with interesting problems, while being invaluable to the organization and enjoy the satisfaction of transforming the way how businesses make decisions. Machine learning and data science is one of the fastest growing and most in demand skills globally and the demand is growing rapidly. Parallel to that, Python is the easiest and most used programming language right now and that's the first language choice when it comes to the machine learning. So, there is no better time to learn machine learning using python than today.I designed this course keeping the beginners and those who with some programming experience in mind. You may be coming from the Finance, Marketing, Engineering, Medical or even a fresher, as long as you have the passion to learn, this course will be your first step to become a Data Scientist.I have 20 hours of best quality video contents. There are over 90 HD video lectures each ranging from 5 to 20 minutes on average. I've included Quizzes to test your knowledge after each topic to ensure you only leave the chapter after gaining the full knowledge. Not only that, I've given you many exercises to practice what you learn and solution to the exercise videos to compare the results. I've included all the exercise notebooks, solution notebooks, data files and any other information in the resource folder.Now, I'm going to answer the most important questions. Why should you choose this course over the other courses?I cover all the important machine learning concepts in this course and beyond.When it comes to machine learning, learning theory is the key to understanding the concepts well. We've given the equal importance to the theory section which most of the other courses don't.We've used the graphical tools and the best possible animations to explain the concepts which we believe to be a key factor that would make you enjoy the course.Most importantly, I've a dedicated section covering all the practical issues you'd face when solving machine learning problems. This is something that other courses tend to ignore.I've set the course price to the lowest possible amount so that anyone can afford the course.Here a just a few of the topics we will be learning:Install Python and setup the virtual environmentLearn the basics of Python programming including variables, lists, tuples, sets, dictionaries, if statements, for loop, while loop, construct a custom function, Python comprehensions, Python built-in functions, Lambda functions and dealing with external libraries.Use Python for Data Science and Machine LearningLearn in-dept theoretical aspects of all the machine learning modelsOpen the data, perform pre-processing activities, build and evaluate the performance of the machine learning models Implement Machine Learning AlgorithmsLearn, Visualization techniques like Matplotlib and SeabornUse SciKit-Learn for Machine Learning TasksK-Means ClusteringDBSCAN ClusteringK-Nearest Neighbors Logistic RegressionLinear RegressionLasso and Ridge - Regularization techniquesRandom Forest and Decision Trees and Extra TreeNaïve Bayes ClassifierSupport Vector MachinesPCA - Principal Component AnalysisBoosting Techniques - Adaboost, Gradient boost, XGBoost, Catboost and LightGBMNatural Language ProcessingHow to deal with the practical problems when dealing with Machine learning
