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所在平台: Udemy |
课程主页: https://www.udemy.com/course/real-world-data-science-projects-to-become-data-scientist/
课程评论：没有评论
**课程名称：** 真实世界数据科学项目助你成为数据科学家 **课程概述：** 本课程旨在帮助您提升数据科学技能，应对真实世界挑战，成为一名优秀的数据科学家。通过五个全面深入的项目，您将掌握数据科学的关键领域： * **客户流失预测（逻辑回归与决策树）：** 学习预测客户流失，掌握混淆矩阵、ROC-AUC等模型评估指标。 * **集成学习在客户流失预测中的应用：** 探索装袋法、提升法、随机森林、AdaBoost和梯度提升等集成学习技术，并使用 LIME 进行模型解释。 * **保险价格预测（XGBoost）：** 构建和评估保险定价模型，学习探索性数据分析、相关性分析，并利用 XGBoost 构建强大模型，通过结果解释做出数据驱动的业务决策。 * **Bigmart 销售预测：** 使用高级技术预测大型零售店的销售情况，从真实数据集中获取洞察，并应用机器学习模型进行准确预测。 **核心内容：** * 使用真实数据集和行业标准工具进行实操。 * 掌握数据可视化、模型结果解释和沟通技巧。 * 通过实际项目构建强大的数据科学作品集。 **建议基础：** * Python 基础知识。 * 基础统计学知识。 **适合人群：** * 有志于成为数据科学家的初学者。 * 希望提升技能的在职专业人士。 * 对构建数据科学项目作品集感兴趣的任何人。 **立即报名，开启您的数据科学学习之旅！**
Are you ready to transform your data science skills and tackle real-world challenges? Welcome to "Real World Data Science Projects to Become Data Scientist," a hands-on course designed to equip you with the knowledge and practical experience needed to excel in the field of data science.In this course, you'll dive deep into five comprehensive projects, each focusing on a crucial aspect of data science:Churn Prediction Using Logistic Regression and Decision Trees: Learn to predict customer churn by implementing logistic regression and decision tree models. Understand key concepts like the confusion matrix, ROC-AUC, and the importance of evaluating model performance.Ensemble Learning for Churn Prediction: Discover the power of ensemble learning techniques. Explore bagging, boosting, Random Forest, AdaBoost, and gradient boosting. Gain hands-on experience with model interpretation using LIME.Insurance Price Prediction Using XGBoost: Develop and evaluate insurance pricing models. Conduct exploratory data analysis, understand correlations, and build robust models using XGBoost. Learn to interpret the results to make data-driven business decisions.Bigmart Sales Prediction: Forecast sales for large retail stores using advanced techniques. Gain insights from real-world datasets and apply machine learning models to predict future sales accurately.Throughout the course, you'll work with real datasets and industry-standard tools, enhancing your practical skills. You'll also learn to visualize data, interpret model results, and communicate insights effectively.This course is perfect for aspiring data scientists, current professionals looking to upgrade their skills, and anyone interested in building a strong portfolio of data science projects. Basic knowledge of Python and familiarity with fundamental statistics are recommended.Enroll now and take the first step towards mastering data science with real-world projects!
