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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-become-kaggle-master/
课程评论：没有评论
课程名称：机器学习A-Z：成为Kaggle大师 概述：想成为一名优秀的数据科学家吗？那么这个课程非常适合你。该课程由IIT的专业人士设计，他们在数学和数据科学方面具有精深的造诣。我们将以简单易懂的方式讲解复杂的理论、算法和编码库，确保任何初学者都能轻松掌握。课程将逐步引导你进入机器学习的世界。每个教程中，你将学习到新技能，并提升对这一具有挑战性但收益丰厚的数据科学子领域的理解，从初学者到进阶水平。我们在课程中解决了一些Kaggle问题，并提供了完整的解决方案，以帮助学生在真实竞争网站上轻松竞争。 课程详细内容包括：1. Python基础 2. Numpy 3. Pandas 4. 数学趣谈 5. 推断统计 6. 假设检验 7. 数据可视化 8. 探索性数据分析（EDA） 9. 简单线性回归 10. 多元线性回归 11. Hotstar/Netflix案例研究 12. 梯度下降 13. KNN 14. 模型性能指标 15. 模型选择 16. 朴素贝叶斯 17. 逻辑回归 18. 支持向量机（SVM） 19. 决策树 20. 集成学习 - 装袋和提升 21. 无监督学习 22. 降维 23. 高级机器学习算法 24. 深度学习。
Want to become a good Data Scientist? Then this is a right course for you.This course has been designed by IIT professionals who have mastered in Mathematics and Data Science. We will be covering complex theory, algorithms and coding libraries in a very simple way which can be easily grasped by any beginner as well.We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science from beginner to advance level.We have solved few Kaggle problems during this course and provided complete solutions so that students can easily compete in real world competition websites.We have covered following topics in detail in this course:1. Python Fundamentals2. Numpy3. Pandas4. Some Fun with Maths5. Inferential Statistics6. Hypothesis Testing7. Data Visualisation8. EDA9. Simple Linear Regression10. Multiple Linear regression11. Hotstar/ Netflix: Case Study12. Gradient Descent13. KNN14. Model Performance Metrics15. Model Selection 16. Naive Bayes17. Logistic Regression18. SVM19. Decision Tree20. Ensembles - Bagging / Boosting21. Unsupervised Learning22. Dimension Reduction23. Advance ML Algorithms24. Deep Learning
