Data Science Bundle
Data Science Projects with Python
- Install the required packages to set up a data science coding environment
- Load data into a Jupyter Notebook running Python
- Use Matplotlib to create data visualizations
- Fit a model using scikit-learn
- Use lasso and ridge regression to reduce overfitting
- Fit and tune a random forest model and compare performance with logistic
- Create visuals using the output of the Jupyter Notebook
Data Science Projects with Python is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The book will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive.
You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You’ll discover how to tune the algorithms to provide the best predictions on new and, unseen data. As you delve into later chapters, you’ll be able to understand the working and output of these algorithms and gain insight into not only the predictive capabilities of the models but also their reasons for making these predictions.
By the end of this book, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from unstructured data.
- Learn techniques to use data to identify the exact problem to be solved
- Visualize data using different graphs
- Identify how to select an appropriate algorithm for data extraction
About this Bundle
Learn essential components of data science & analysis development workflow for all your complex programming needs with the Data Science Bundle.
In this collection of 20 easy-to-follow eBooks across three tiers, featuring 15 new-to-Fanatical titles, you’ll tackle the most sophisticated problems and use the likes of Python and its extensive libraries to power your way to new levels of data insight, as well as applying data science to successful marketing campaigns.
In Tier One, you’ll receive five eBooks featuring a series of quick start guides to get you up and running with user interfaces and open-source tools such as Kibana 7, JupyterLab and PySpark. With Data Science Projects with Python, you’ll learn techniques to use data to identify the exact problem to be solved, and identify how to select an appropriate algorithm for data extraction.
With Tier Two, you’ll not only get Tier One’s content, but also an additional five eBooks, with hands-on knowledge for budding data scientists, data enthusiasts and R developers. Following the guidance of Hands-On Data Analysis with Pandas, you’ll combine, group, and aggregate data from multiple sources, as well as build Python scripts, modules, and packages for reusable analysis code.
Opt for Tier Three and you’ll receive all 20 eBooks in this bundle, expanding your analytical horizons. With Data Analysis with R - Second Edition, you’ll gain a thorough understanding of statistical reasoning and sampling theory, and learn how to scale your analyses to larger data with Rcpp, data.table, dplyr, and parallelization.
The eBooks in this bundle are available in EPUB, MOBI and PDF formats.