Data Science Projects with Python: A case study approach to successful data science projects using Python, pandas, and scikit-learn
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Gain hands-on experience with industry-standard data analysis and machine learning tools in Python
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
Book Description
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.
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
Who this book is for
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.
Table of Contents
- Data Exploration and Cleaning
- Introduction to Scikit-Learn and Model Evaluation
- Details of Logistic Regression and Feature Exploration
- The Bias-Variance Trade-off
- Decision Trees and Random Forests
- Imputation of Missing Data, Financial Analysis, and Delivery to Client
From the Publisher
About Data Science Projects with Python
Data Science Projects with Python is a hands-on introduction to real-world data science. You’ll take an active approach to learning by following real case studies that elegantly tie together mathematics and code.
You’ll start by learning how to examine, extract and present insights from your own data with tools like pandas and Matplotlib. You’ll build upon these skills as you start feeding data into machine learning algorithms with sci-kit learn, tuning them individually as you learn how they make their predictions.
Data Science Projects with Python is ideal if you’re looking for guidance on industry-standard data analysis and machine learning tools. You’ll learn how to navigate your own unstructured data, extracting meaningful insights along the way.
Key Features
Ideal introduction to data science for those already familiar with foundational Python
Full of practical step-by-step exercises, activities and solutions
Structured to let you pause and progress learning on your terms
Learn Real-World Data Science
Real-World Exercises and Activities
You’ll complete step-by-step exercises that build practical, hands-on skills. Activities then challenge you to apply and extend your new abilities. It’s a proven structure that’s designed to hack your brain and embed your learning.
Learning On Your Terms
It can be tough to manage learning around your existing commitments. With a structure that lets you pick up and progress at your own pace, you’re far more likely to reach your goal. It’s time to take back control of your schedule.
Developed by Trusted Experts
Every project brings together a team of expert authors, instructors, and technical editors. You’ll find step-by-step guidance from start to finish, complete with worked solutions. You won’t ever be stuck with an example that doesn’t compile.
