Scikit-learn in Python: 100+ Data Science Exercises

Master Machine Learning - Unleash the Power of Data Science for Predictive Modeling!

Created by: Paweł Krakowiak
Python Developer/Data Scientist/Stockbroker

What Will I 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

Requirements

• completion of all courses in the Python Developer learning path
• completion of all courses in the Data Scientist learning path
• basic knowledge of NumPy, Pandas & Scikit-learn

Target audience

• 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