AWS Certified Machine Learning: Jupyter Notebook & Python
Amazon Web Services
| Intermediate
- 13 videos | 38m 50s
- Includes Assessment
- Earns a Badge
Exploring and analyzing data to comprehend its underlying characteristics and patterns becomes increasingly vital as vaster amounts are collected. This is key in formulating the most suitable problems, the solving of which helps achieve real-world business goals. Use this course to get your head around the programming fundamentals for machine learning in AWS, which form the basis for most data exploratory steps on the AWS platform. Explore various Python packages used in machine learning and data analysis and become familiar with Jupyter Notebook's fundamental concepts. Then, work with Python and Jupyter Notebook to create a machine learning model. When you're done, you'll be able to use Jupyter Notebook and various Python packages in machine learning and data analysis. You'll be one step closer to being prepared for the AWS Certified Machine Learning - Specialty certification exam.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this courseDescribe the basic features and use cases of jupyter notebook related to data cleaning, transformation, visualization, and machine learningName python data analysis packages and describe their functionalityDescribe how the numpy package is used for data analysisDescribe how the pandas package is used for data analysisWork with the numpy package functionalities for solving data analysis tasksWork with the pandas package functionalities for solving data analysis tasks
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Outline how the matplotlib package is used for data analytics and visualizationOutline how seaborn and bokeh packages are used for data analysisWork with matplotlib, seaborn, and bokeh packages to solve data analysis tasksSpecify how the scikit-learn package is used for classification, regression, clustering, and other tasksWork with python toolkits to tackle a real-world data analysis problemSummarize the key concepts covered in this course
IN THIS COURSE
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1m 10s
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2m 35sFind out how to describe the basic features and use cases of Jupyter Notebook related to data cleaning, transformation, visualization, and machine learning. FREE ACCESS
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2m 27sLearn how to name and describe the functionality of Python data analysis packages. FREE ACCESS
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1m 37sIn this video, you will learn how to describe how to use the NumPy package for data analysis. FREE ACCESS
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1m 21sDuring this video, you will discover how the Pandas package is used for data analysis. FREE ACCESS
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5m 37sIn this video, discover how to work with the NumPy package to solve data analysis tasks. FREE ACCESS
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6m 28sDiscover how to work with the Pandas package to solve data analysis tasks. FREE ACCESS
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1m 15sIn this video, you will outline how to use the Matplotlib package for data analytics and visualization. FREE ACCESS
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1m 29sAfter completing this video, you will be able to outline how to use Seaborn and Bokeh packages for data analysis. FREE ACCESS
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6m 31sIn this video, find out how to work with the Matplotlib, Seaborn, and Bokeh packages to solve data analysis tasks. FREE ACCESS
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1m 48sUpon completion of this video, you will be able to specify how the scikit-learn package is used for classification, regression, clustering, and other tasks. FREE ACCESS
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5m 50sDuring this video, you will learn how to work with Python toolkits to solve a real-world data analysis problem. FREE ACCESS
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43sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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