Machine Learning Essentials - Master core ML concepts

所在平台: Udemy

课程主页: https://www.udemy.com/course/machine-learning-artificial-intelligence-essentials/

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课程名称:机器学习基础 - 掌握核心机器学习概念 课程概述:你准备好踏入机器学习与人工智能的世界吗?本课程专为绝对初学者和希望利用机器学习解决实际问题的熟练程序员设计。您将学习如何处理数据,并训练能够做出“智能决策”的模型。数据科学是21世纪最有前途的职业之一,财富500强科技公司在数据科学家方面的投资亦非常可观,因此,数据科学职业也提供世界上最高的薪资之一。 与其他仅覆盖库实现的课程不同,本课程旨在为您提供坚实的机器学习基础,涵盖数学知识和从零开始的 Python 实现,涉及大多数统计技术。课程由Prateek Narang和Mohit Uniyal教授,二位不仅是受欢迎的讲师,还曾在谷歌等公司从事软件工程和数据科学工作,教授了数千名学生。 本课程以其极具行动导向的特点而著称,不仅深入理论,还注重实践,通过构建8个以上项目进行学习。课程中包含超过170节高质量视频讲座,易于理解的解释和完整的代码库,是学习数据科学的最详细和最全面的课程之一。 课程内容包括: - 逻辑回归 - 线性回归 - 主成分分析 - 朴素贝叶斯 - 决策树 - 装袋与提升 - K近邻 - K均值 - 神经网络 您将学习的概念还包括: - 凸优化 - 过拟合与欠拟合 - 偏差方差权衡 - 性能指标 - 数据预处理 - 特征工程 - 处理数值数据、图像和文本数据 - 参数化与非参数化技术 立即注册课程,迈出成为机器学习工程师的第一步!期待在课程中见到你!

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Read to jumpstart the world of Machine Learning & Artificial intelligence?This hands-on course is designed for absolute beginners as well as for proficient programmers who want kickstart Machine Learning for solving real life problems. You will learn how to work with data, and train models capable of making "intelligent decisions" Data Science has one of the most rewarding jobs of the 21st century and fortune-500 tech companies are spending heavily on data scientists! Data Science as a career is very rewarding and offers one of the highest salaries in the world. Unlike other courses, which cover only library-implementations this course is designed to give you a solid foundation in Machine Learning by covering maths and implementation from scratch in Python for most statistical techniques.This comprehensive course is taught by Prateek Narang & Mohit Uniyal, who not just popular instructors but also have worked in Software Engineering and Data Science domains with companies like Google. They have taught thousands of students in several online and in-person courses over last 3+ years. We are providing you this course to you at a fraction of its original cost! This is action oriented course, we not just delve into theory but focus on the practical aspects by building 8+ projects. With over 170+ high quality video lectures, easy to understand explanations and complete code repository this is one of the most detailed and robust course for learning data science.Some of the topics that you will learn in this course.Logistic RegressionLinear RegressionPrincipal Component AnalysisNaive BayesDecision TreesBagging and BoostingK-NNK-MeansNeural NetworksSome of the concepts that you will learn in this course.Convex OptimisationOverfitting vs UnderfittingBias Variance TradeoffPerformance MetricsData Pre-processingFeature EngineeringWorking with numeric data, images & textual dataParametric vs Non-Parametric TechniquesSign up for the course and take your first step towards becoming a machine learning engineer! See you in the course!

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