Scikit-learn in Python: 100+ Data Science Exercises

Scikit-learn in Python: 100+ Data Science Exercises, available at $64.99, has an average rating of 5, with 114 lectures, 102 quizzes, based on 93 reviews, and has 40162 subscribers.

You will learn about solve over 100 exercises in numpy, pandas and scikit-learn deal with real programming problems in data science work with documentation and Stack Overflow guaranteed instructor support This course is ideal for individuals who are data scientists or machine learning practitioners who want to enhance their skills in using the Scikit-learn library for building and evaluating machine learning models in Python or students or individuals with a background in data science, machine learning, or related fields who want to gain hands-on experience in applying machine learning techniques using Scikit-learn or programmers or software developers who are interested in data science and want to learn how to use Scikit-learn for tasks such as data preprocessing, model training, and evaluation or professionals working in industries such as finance, healthcare, or marketing, where machine learning is applied, and who want to learn how to leverage Scikit-learn for their data analysis and modeling needs or self-learners who are passionate about data science and want to develop proficiency in using Scikit-learn for various machine learning tasks, including classification, regression, clustering, and model evaluation or researchers or scientists who want to apply machine learning techniques to their research problems and utilize Scikit-learn as a tool for model building and evaluation It is particularly useful for data scientists or machine learning practitioners who want to enhance their skills in using the Scikit-learn library for building and evaluating machine learning models in Python or students or individuals with a background in data science, machine learning, or related fields who want to gain hands-on experience in applying machine learning techniques using Scikit-learn or programmers or software developers who are interested in data science and want to learn how to use Scikit-learn for tasks such as data preprocessing, model training, and evaluation or professionals working in industries such as finance, healthcare, or marketing, where machine learning is applied, and who want to learn how to leverage Scikit-learn for their data analysis and modeling needs or self-learners who are passionate about data science and want to develop proficiency in using Scikit-learn for various machine learning tasks, including classification, regression, clustering, and model evaluation or researchers or scientists who want to apply machine learning techniques to their research problems and utilize Scikit-learn as a tool for model building and evaluation.

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Summary

Title: Scikit-learn in Python: 100+ Data Science Exercises

Price: $64.99

Average Rating: 5

Number of Lectures: 114

Number of Quizzes: 102

Number of Published Lectures: 114

Number of Published Quizzes: 102

Number of Curriculum Items: 216

Number of Published Curriculum Objects: 216

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

• solve over 100 exercises in numpy, pandas and scikit-learn
• deal with real programming problems in data science
• work with documentation and Stack Overflow
• guaranteed instructor support

Who Should Attend

• data scientists or machine learning practitioners who want to enhance their skills in using the Scikit-learn library for building and evaluating machine learning models in Python
• students or individuals with a background in data science, machine learning, or related fields who want to gain hands-on experience in applying machine learning techniques using Scikit-learn
• programmers or software developers who are interested in data science and want to learn how to use Scikit-learn for tasks such as data preprocessing, model training, and evaluation
• professionals working in industries such as finance, healthcare, or marketing, where machine learning is applied, and who want to learn how to leverage Scikit-learn for their data analysis and modeling needs
• self-learners who are passionate about data science and want to develop proficiency in using Scikit-learn for various machine learning tasks, including classification, regression, clustering, and model evaluation
• researchers or scientists who want to apply machine learning techniques to their research problems and utilize Scikit-learn as a tool for model building and evaluation

Target Audiences

• data scientists or machine learning practitioners who want to enhance their skills in using the Scikit-learn library for building and evaluating machine learning models in Python
• students or individuals with a background in data science, machine learning, or related fields who want to gain hands-on experience in applying machine learning techniques using Scikit-learn
• programmers or software developers who are interested in data science and want to learn how to use Scikit-learn for tasks such as data preprocessing, model training, and evaluation
• professionals working in industries such as finance, healthcare, or marketing, where machine learning is applied, and who want to learn how to leverage Scikit-learn for their data analysis and modeling needs
• self-learners who are passionate about data science and want to develop proficiency in using Scikit-learn for various machine learning tasks, including classification, regression, clustering, and model evaluation
• researchers or scientists who want to apply machine learning techniques to their research problems and utilize Scikit-learn as a tool for model building and evaluation