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The Applied Data Science Workshop
最新章節(jié):
6. Web Scraping with Jupyter Notebooks
Frombankingandmanufacturingthroughtoeducationandentertainment,usingdatascienceforbusinesshasrevolutionizedalmosteverysectorinthemodernworld.Ithasanimportantroletoplayineverythingfromappdevelopmenttonetworksecurity.Takinganinteractiveapproachtolearningthefundamentals,thisbookisidealforbeginners.You’lllearnallthebestpracticesandtechniquesforapplyingdatascienceinthecontextofreal-worldscenariosandexamples.Startingwithanintroductiontodatascienceandmachinelearning,you’llstartbygettingtogripswithJupyterfunctionalityandfeatures.You’llusePythonlibrarieslikesci-kitlearn,pandas,Matplotlib,andSeaborntoperformdataanalysisanddatapreprocessingonreal-worlddatasetsfromwithinyourownJupyterenvironment.Progressingthroughthechapters,you’lltrainclassificationmodelsusingsci-kitlearn,andassessmodelperformanceusingadvancedvalidationtechniques.Towardstheend,you’lluseJupyterNotebookstodocumentyourresearch,buildstakeholderreports,andevenanalyzewebperformancedata.BytheendofTheAppliedDataScienceWorkshop,you’llbepreparedtoprogressfrombeingabeginnertotakingyourskillstothenextlevelbyconfidentlyapplyingdatasciencetechniquesandtoolstoreal-worldprojects.
目錄(41章)
倒序
- 封面
- 版權信息
- Preface
- 1. Introduction to Jupyter Notebooks
- Introduction
- Basic Functionality and Features of Jupyter Notebooks
- Jupyter Features
- Summary
- 2. Data Exploration with Jupyter
- Introduction
- Our First Analysis – the Boston Housing Dataset
- Summary
- 3. Preparing Data for Predictive Modeling
- Introduction
- Machine Learning Process
- Approaching Data Science Problems
- Understanding Data from a Modeling Perspective
- Introducing the Human Resource Analytics Dataset
- Summary
- 4. Training Classification Models
- Introduction
- Understanding Classification Algorithms
- Summary
- 5. Model Validation and Optimization
- Introduction
- Assessing Models with k-Fold Cross Validation
- Dimensionality Reduction with PCA
- Summary
- 6. Web Scraping with Jupyter Notebooks
- Introduction
- Internet Data Sources
- Introduction to HTTP Requests
- Data Workflow with pandas
- Summary
- Appendix
- 1. Introduction to Jupyter Notebooks
- 2. Data Exploration with Jupyter
- 3. Preparing Data for Predictive Modeling
- 4. Training Classification Models
- 5. Model Validation and Optimization
- 6. Web Scraping with Jupyter Notebooks 更新時間:2021-06-18 18:27:46
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