【课程】Python数据科学-技术详解与商业实践（八大案例，配套书籍） - 带源码课件 mp4 [4.9GB]
<section class="ybc-p" style="color: #000000; font-family: 微软雅黑, 宋体, Arial, Helvetica, sans-serif; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; white-space: normal; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"><span style="font-size: 16px;"><strong>【天善智能】Python数据科学 - 技术详解与商业实践（八大案例，配套书籍）</strong><span> </span>是一套聚焦<span> </span><strong>Python数据科学全流程应用</strong><span> </span>的实战型学习资源，涵盖从基础技术解析到商业场景落地的完整知识体系，并提供<span> </span><strong>八大真实案例、配套书籍及全套源码课件</strong><span> </span>，助力学员快速掌握数据驱动决策的核心技能。</span></section><p style="margin: 5px 0px; color: #000000; font-family: 微软雅黑, 宋体, Arial, Helvetica, sans-serif; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; white-space: normal; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"> </p>
<section class="ybc-p"><span style="font-size: 16px;">课程以<span> </span><strong>“技术+商业”双主线</strong><span> </span>展开：技术层面系统讲解Python数据科学核心工具链——从NumPy/Pandas的数据清洗与预处理、Matplotlib/Seaborn的可视化分析，到Scikit-learn的机器学习建模、XGBoost/LightGBM的高级算法应用，再到深度学习框架（如PyTorch/TensorFlow）在数据科学中的延伸使用；商业实践部分精选<span> </span><strong>八大行业典型案例</strong><span> </span>（如零售客户分群、金融风控建模、电商销量预测、医疗数据分析等），每个案例均基于真实业务场景设计，涵盖数据采集、特征工程、模型训练、效果评估到决策建议的全流程，配套书籍深度解析技术原理与业务逻辑关联。</span></section>
<section class="ybc-p"><span style="font-size: 16px;">资源包提供<span> </span><strong>完整源码与课件</strong><span> </span>，支持边学边练，帮助学员快速将理论转化为解决实际问题的能力，是数据分析师、Python开发者及商业决策者提升数据科学实战能力的优质选择。 </span></section>
<section class="ybc-p"><span style="font-size: 16px;">（注：案例与代码适配主流行业需求，注重实用性与可复现性。）</span></section>
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