Python Data Science Essentials: A practitioner’s guide covering essential data science principles, tools, and techniques, 3rd Edition
By 作者: Alberto Boschetti – Luca Massaron
ISBN-10 书号: 178953786X
ISBN-13 书号: 9781789537864
Release Finelybook 出版日期: 2018-10-09
pages 页数: (472 )
Book Description to Finelybook sorting
Fully expanded and upgraded, the latest edition of Python Data Science Essentials will help you succeed in data science operations using the most common Python libraries. This book offers up-to-date insight into the core of Python, including the latest versions of the Jupyter Notebook, NumPy, pandas, and scikit-learn.
The book covers detailed examples and large hybrid datasets to help you grasp essential statistical techniques for data collection, data munging and analysis, visualization, and reporting activities. You will also gain an understanding of advanced data science topics such as machine learning algorithms, distributed computing, tuning predictive models, and natural language processing. Furthermore, You’ll also be introduced to deep learning and gradient boosting solutions such as XGBoost, LightGBM, and CatBoost.
By the end of the book, you will have gained a complete overview of the principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users.
1: FIRST STEPS
2: DATA MUNGING
3: THE DATA PIPELINE
4: MACHINE LEARNING
5: VISUALIZATION, INSIGHTS, AND RESULTS
6: SOCIAL NETWORK ANALYSIS
7: DEEP LEARNING BEYOND THE BASICS
8: SPARK FOR BIG DATA
What You Will Learn
Set up your data science toolbox on Windows, Mac, and Linux
Use the core machine learning methods offered by the scikit-learn library
Manipulate, fix, and explore data to solve data science problems
Learn advanced explorative and manipulative techniques to solve data operations
Optimize your machine learning models for optimized performance
Explore and cluster graphs, taking advantage of interconnections and links in your data
Alberto Boschetti is a data scientist with expertise in signal processing and statistics. He holds a Ph.D. in telecommunication engineering and currently lives and works in London. In his work projects, he faces challenges ranging from natural language processing (NLP) and behavioral analysis to machine learning and distributed processing. He is very passionate about his job and always tries to stay updated about the latest developments in data science technologies, attending meet-ups, conferences, and other events.
Luca Massaron is a data scientist and marketing research director specialized in multivariate statistical analysis, machine learning, and customer insight, with over a decade of experience of solving real-world problems and generating value for stakeholders by applying reasoning, statistics, data mining, and algorithms. From being a pioneer of web audience analysis in Italy to achieving the rank of a top-10 Kaggler, he has always been very passionate about every aspect of data and its analysis, and also about demonstrating the potential of data-driven knowledge discovery to both experts and non-experts. Favoring simplicity over unnecessary sophistication, Luca believes that a lot can be achieved in data science just by doing the essentials.