🌚接着,我开始了第四门课——Python for Data Science, AI & Development。目前卡在第二周的实验室作业。原因是IBM的JupyterLab系统在进行维护,从上周五到今天(一周)都无法进入实验室,具体何时能解决问题还不确定。这门课主要讲解Python,不上实验室作业根本无法进行下去,真是让人无语。我打算去申请退款,耽误的...
IBM数据科学专业证书课程4:《Python应用于数据科学、人工智能和开发》python-for-applied-data-science-ai(中英字幕)共计24条视频,包括:0_类型.zh_en、1_表达式和变量.zh_en、2_字符串操作.zh_en等,UP主更多精彩视频,请关注UP账号。
Python for Data Science and AI Data Analysis with Python Applied Data Science Capstone Databases and SQL for Data Science Tools for Data Science Data Visualization with Python Coursera官方建议总课程有十个月的跨度,但我亲测除了Capstone外,其余课程一天内都能搞定。Capstone因为作业比较复杂,我用了四天时间...
> Course 4: Python for Data Science 这门是Python基础,配有很多Lab课演示代码。最后的大作业是使用pandas library导入并查看数据,以及通过自定义function建一个dashboard,看似复杂,但大部分的代码其实老师都写好了,基本只要根据instruction填填空就行了,比较简单... 画出这个图还不算完事,最后IBM还硬要来炫个技...
> Course 1:What is Data Science? > Course 2: Tools for Data Science > Course 3: Data Science Methodology > Course 4: Python for Data Science and AI > Course 5: Databases and SQL for Data Science > Course 6: Data Analysis with Python ...
Python for Data Science, AI & Development:掌握Python编程,为数据科学和人工智能打下基础。 Databases and SQL for Data Science with Python:用Python连接数据库,进行数据查询和分析。 Data Analysis with Python:用Python进行数据分析和建模。 Data Visualization with Python:用Python进行数据可视化,制作各种图表。
单击Data Science and MLOps 项目名称。单击"资产"选项卡,然后导航至笔记本。 注: 如果您看到警告图标,然后单击溢出菜单在monitor-wml-model-with-watson-openscale-pipeline 笔记本旁边,选择 “更改环境”。 Python选择支持的运行时,然后点击 “更改”。打开...
Python for Data Science, AI & Development Python Project for Data Science Databases and SQL for Data Science with Python Data Analysis with Python Data Visualization with Python IBM Data Analyst Capstone Project 課程簡介 在第1堂課的基礎學習中,你除了可以學到數據分析的基礎,還可以在第五周的課程中,...
Python for Data Science and AI -- Week 1 This Python course consists of the following modules: Python basics, Python data structures, Python programming fundamentals, working with Data in Python, final project. Quiz What is the type of the following: 1.0? --float ...
Lale is a Python library for semi-automated data science. Lale makes it easy to automatically select algorithms and tune hyperparameters of pipelines that are compatible with scikit-learn, in a type-safe fashion. If you are a data scientist who wants to experiment with automated machine learning...