Beginning Data Science Python by Galea Alex (12 results)

Paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

paperback. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority!

Condition: Very Good. Used book that is in excellent condition. May show signs of wear or have minor defects.

Condition: New.

Condition: New.

Condition: New.

Digital. Condition: New. Getting started with data science doesn't have to be an uphill battle. This step-by-step guide is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction.About This Book. Get up and running with the Jupyter ecosystem and some example datasets. Learn about key machine learning concepts like SVM, KNN classifiers and Random Forests. Discover how you can use web scraping to gather and parse your own bespoke datasets Who This Book Is ForThis book is ideal for professionals with a variety of job descriptions across large range of industries, given the rising popularity and accessibility of data science. You'll need some prior experience with Python, with any prior work with libraries like Pandas, Matplotlib and Pandas providing you a useful head start.What You Will Learn. Identify potential areas of investigation and perform exploratory data analysis. Plan a machine learning classification strategy and train classification models. Use validation curves and dimensionality reduction to tune and enhance your models. Scrape tabular data from web pages and transform it into Pandas DataFrames. Create interactive, web-friendly visualizations to clearly communicate your findings In DetailGet to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world. We'll finish up by showing you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context.Style and approachThis book covers every aspect of the standard data-workflow process within a day, along with theory, practical hands-on coding, and relatable illustrations.

Condition: New. In.

Paperback. Condition: New.

Digital. Condition: New. Getting started with data science doesn't have to be an uphill battle. This step-by-step guide is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction.About This Book. Get up and running with the Jupyter ecosystem and some example datasets. Learn about key machine learning concepts like SVM, KNN classifiers and Random Forests. Discover how you can use web scraping to gather and parse your own bespoke datasets Who This Book Is ForThis book is ideal for professionals with a variety of job descriptions across large range of industries, given the rising popularity and accessibility of data science. You'll need some prior experience with Python, with any prior work with libraries like Pandas, Matplotlib and Pandas providing you a useful head start.What You Will Learn. Identify potential areas of investigation and perform exploratory data analysis. Plan a machine learning classification strategy and train classification models. Use validation curves and dimensionality reduction to tune and enhance your models. Scrape tabular data from web pages and transform it into Pandas DataFrames. Create interactive, web-friendly visualizations to clearly communicate your findings In DetailGet to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world. We'll finish up by showing you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context.Style and approachThis book covers every aspect of the standard data-workflow process within a day, along with theory, practical hands-on coding, and relatable illustrations.

Condition: New. Print on Demand pp. 194.

Paperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 380.