Develop-Packt's repositories
An-Introduction-to-Data-Visualization-and-Data-Exploration-with-Python
Learn the fundamental concepts of data wrangling and statistics, and understand how they relate to data visualization.
Creating-Plots-with-Matplotlib
Discover how to use Matplotlib to create visualizations using the built-in plots that are provided by the library. Customize your visualizations and write mathematical expressions using TeX.
Creating-Ensemble-Models-with-Python
Recognize underfitting and overfitting, implement bagging and boosting, and build a stacked ensemble model using a number of classifiers.
Cross-Validation-and-Keras-Wrappers
Study the form and function of two major cross-validation methods, build a scikit learn interface, and use cross-validation to perform image classification and selection on example datasets
Evaluating-Supervised-Learning-Models-with-Python
Measure model performance using various metrics. Use sampling and hyperparameter tuning to improve models, and calculate feature importance for model evaluation.
Exploring-and-Visualizing-Data-with-Python
Perform exploratory data analysis to visualize the distribution of values in a dataset, analyze relationships using correlation, and locate and fix data problems including missing values.
Introduction-to-Supervised-Learning-with-Python
Discover the key concepts of supervised learning and learn to load, manipulate and describe data with key Python packages.
Performing-Linear-Regression-with-Python
Implement gradient descent in linear regression problems, construct and evaluate simple linear models, and use feature engineering to create more complex supervised machine learning models.
Plotting-Geospatial-Data
Utilize Geoplotlib to create stunning geographical visualizations, identify the different types of geospatial charts, and create complex visualizations using tile providers and custom layers.
Simplifying-Visualizations-Using-Seaborn
Learn how to create visually appealing and insightful plots efficiently using Seaborn.