Statistical Data Visualization with Seaborn

4.3
звезд
Оценки: 16
Рецензии: 4
от партнера
Rhyme
В этом Guided Project вы:

Produce and customize various chart types with Seaborn

Apply feature selection and feature extraction methods with scikit-learn

Build a boosted decision tree classifier with XGBoost

Clock1.5 hours
IntermediateУчащийся среднего уровня
CloudЗагрузка не требуется
VideoВидео на разделенном экране
Comment DotsАнглийский
LaptopТолько для ПК

Welcome to this project-based course on Statistical Data Visualization with Seaborn. Producing visualizations is an important first step in exploring and analyzing real-world data sets. As such, visualization is an indispensable method in any data scientist's toolbox. It is also a powerful tool to identify problems in analyses and for illustrating results. In this project, we will employ the statistical data visualization library, Seaborn, to discover and explore the relationships in the Breast Cancer Wisconsin (Diagnostic) data set. We will use the results from our exploratory data analysis (EDA) in the previous project, Breast Cancer Diagnosis – Exploratory Data Analysis to: drop correlated features, implement feature selection and feature extraction methods including feature selection with correlation, univariate feature selection, recursive feature elimination, principal component analysis (PCA) and tree based feature selection methods. Lastly, we will build a boosted decision tree classifier with XGBoost to classify tumors as either malignant or benign. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit-learn pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Навыки, которые вы получите

Data ScienceMachine LearningPython ProgrammingSeabornData Visualization (DataViz)

Будете учиться пошагово

На видео, которое откроется рядом с рабочей областью, преподаватель объяснит эти шаги:

  1. Project Overview

  2. Importing Libraries and Data

  3. Dropping Correlated Columns from Feature List

  4. Classification using XGBoost (minimal feature selection)

  5. Univariate Feature Selection

  6. Recursive Feature Elimination with Cross-Validation

  7. Plot CV Scores vs Number of Features Selected

  8. Feature Extraction using Principal Component Analysis

How Guided Projects work

Ваше рабочее пространство — это облачный рабочий стол в браузере. Ничего не нужно загружать.

На разделенном экране видео преподаватель предоставляет пошаговые

Часто задаваемые вопросы

Часто задаваемые вопросы

  • By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.

  • Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.

  • Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.

  • You can download and keep any of your created files from the Guided Project. To do so, you can use the “File Browser” feature while you are accessing your cloud desktop.

  • Financial aid is not available for Guided Projects.

  • Auditing is not available for Guided Projects.

  • At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.

  • Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.

  • Вы научитесь выполнять задания в режиме разделенного экрана непосредственно в браузере. В левой части экрана можно выполнять задания в своем рабочем пространстве. В правой части экрана можно просматривать пошаговые инструкции преподавателя по работе с проектом.

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