Data Science Projects with Python is designed to give you practical guidance on industry-standard data analysis and machine learning tools, by applying them to realistic data problems. You will learn how to use pandas and Matplotlib to critically examine datasets with summary statistics and graphs, and extract the insights you seek to derive. You will build your knowledge as you prepare data using the scikit-learn package and feed it to machine learning algorithms such as regularized logistic regression and random forest. You’ll discover how to tune algorithms to provide the most accurate predictions on new and unseen data. As you progress, you’ll gain insights into the working and output of these algorithms, building your understanding of both the predictive capabilities of the models and why they make these predictions.
By then end of this book, you will have the necessary skills to confidently use machine learning algorithms to perform detailed data analysis and extract meaningful insights from unstructured data.
publication date
2019-04-30
what you will learn
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 machine learning models using scikit-learn
Use lasso and ridge regression to regularize your models
Compare performance between models to find the best outcomes
Use k-fold cross-validation to select model hyperparameters
key features
Tackle data science problems by identifying the problem to be solved * Illustrate patterns in data using appropriate visualizations * Implement suitable machine learning algorithms to gain insights from data
approach
Data Science Projects with Python takes a hands-on case study approach to simulate the working conditions you will experience when applying data science and machine learning techniques. You will be presented with a problem and a data set, and follow a practical walkthrough to define an answerable question, decide what analysis methods to use, and implement your chosen methods with Python.
audience
If you are a data analyst, data scientist, or business analyst who wants to get started using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of Python and data analytics will help you get the most from this book. Familiarity with mathematical concepts such as algebra and basic statistics will also be useful.
short description
Data Science Projects with Python will help you build a toolkit for solving data science problems with Python. You will learn how to implement machine learning techniques for deriving insights from data. These skills will help you develop the kind of state-of-the-art predictive models that are used to deliver value to businesses across industries.
subtitle
A case study approach to successful data science projects using Python, pandas, and scikit-learn
keywords
Python, Matplotlib, NumPy, SciPy, BeautifulSoup, Pandas, Data Science, case study, data visualization
Product ISBN
9781838551025
