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Reseña del curso Master Regression & Prediction with Pandas and Python [2026] de Henrik Johansson

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Learn to Master Regression and Prediction with Pandas and Python for Data Science, Data Analysis, and Machine Learning

Formato de aprendizaje Online Course

Subcategoría Python

Precio del curso $19.99

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Sobre Henrik Johansson

Learn to Master Regression and Prediction with Pandas and Python for Data Science, Data Analysis, and Machine Learning

¿Quién es Henrik Johansson?

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Sector

Development

Total de estudiantes

4,321 students

Sitio web oficial

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Idioma del curso

English

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¿Qué se aprende en el curso de Henrik Johansson?

Master Regression, Regression analysis, and Prediction both in theory and practice

Master Regression models from simple Regression models to Polynomial Multiple Regression models and advanced Multivariate Polynomial Multiple Regression models

Use Machine Learning Automatic Model Creation and Feature Selection

Use Regularization of Regression models with Lasso Regression and Ridge Regression

Use Decision Tree, Random Forest, XGBoost, and Voting Regression models

Use Feedforward Multilayer Networks and Advanced Regression model Structures

Use effective advanced Residual analysis and tools to judge models goodness-of-fit plus residual distributions

Use the Statsmodels and Scikit-learn libraries for Regression supported by Matplotlib, Seaborn, Pandas, and Python

Master Python 3 programming with Python’s native data structures, data transformers, functions, object orientation, and logic

Use and design advanced Python constructions and execute detailed Data Handling tasks with Python incl. File Handling

Use Python’s advanced object-oriented programming and make your own custom objects, functions and how to generalize functions

Manipulate data and use advanced multi-dimensional uneven data structures

Master the Pandas 2 and 3 library for Advanced Data Handling

Use the language and fundamental concepts of the Pandas library and to handle all aspects of creating, changing, modifying, and selecting Data from a Pandas D

Use file handling with Pandas and how to combine Pandas DataFrames with Pandas concat, join, and merge functions/methods

Perform advanced data preparation including advanced model-based imputation of missing data and the scaling and standardizing of data

Make advanced data descriptions and statistics with Pandas. Rank, sort, cross-tabulate, pivot, melt, transpose, and group data

[Bonus] Make advanced Data Visualizations with Pandas, Matplotlib, and Seaborn

Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources

Option: To use the Anaconda Distribution (for Windows, Mac, Linux)

Option: Use Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages

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