Data Analysis with Python: A Modern Approach

Learn a modern approach to data analysis using Python to harness the power of programming and AI across your data. Detailed case studies bring this modern approach to life across visual data, social media, graph algorithms, and time series analysis.

Key Features

• Bridge your data analysis with the power of programming, complex algorithms, and AI
• Use Python and its extensive libraries to power your way to new levels of data insight
• Work with AI algorithms, TensorFlow, graph algorithms, NLP, and financial time series
• Explore this modern approach across with key industry case studies and hands-on projects

Book Description

Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects.

Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you're likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence.

What you will learn

• A new toolset that has been carefully crafted to meet for your data analysis challenges
• Full and detailed case studies of the toolset across several of today's key industry contexts
• Become super productive with a new toolset across Python and Jupyter Notebook
• Look into the future of data science and which directions to develop your skills next

Who this book is for

This book is for developers wanting to bridge the gap between them and data scientists. Introducing PixieDust from its creator, the book is a great desk companion for the accomplished Data Scientist. Some fluency in data interpretation and visualization is assumed. It will be helpful to have some knowledge of Python, using Python libraries, and some proficiency in web development.

Table of Contents

1. Programming and Data Science – A New Toolset
2. Python and Jupyter Notebooks to Power your Data Analysis
3. Accelerate your Data Analysis with Python Libraries
4. Publish your Data Analysis to the Web - the PixieApp Tool
5. Python and PixieDust Best Practices and Advanced Concepts
6. Analytics Study: AI and Image Recognition with TensorFlow
7. Analytics Study: NLP and Big Data with Twitter Sentiment Analysis
8. Analytics Study: Prediction - Financial Time Series Analysis and Forecasting
9. Analytics Study: Graph Algorithms - US Domestic Flight Data Analysis
10. The Future of Data Analysis and Where to Develop your Skills

學習使用Python進行現代數據分析的方法，利用編程和人工智能的力量來處理數據。詳細的案例研究將展示這種現代方法在視覺數據、社交媒體、圖形算法和時間序列分析等領域的應用。

主要特點：
- 將數據分析與編程、複雜算法和人工智能相結合
- 使用Python及其豐富的庫來提升數據洞察力
- 使用人工智能算法、TensorFlow、圖形算法、自然語言處理和金融時間序列進行工作
- 通過關鍵行業案例研究和實踐項目來探索這種現代方法

《書籍描述》
《Python數據分析》提供了一種現代方法，讓您能夠使用最新和最強大的Python工具、人工智能技術和開源庫進行數據分析。行業專家David Taieb向您展示如何將數據科學與編程和算法的力量相結合。您將使用複雜的算法和尖端的人工智能進行數據分析。通過使用基於Python的工具和Jupyter Notebook的實際示例來學習如何分析數據。您將找到理論和實踐的平衡，並且可以將廣泛的代碼文件整合到自己的數據項目中。

通過在關鍵行業案例研究中使用這種數據分析方法的力量來探索。四個引人入勝的完整項目將使您與當今最重要的數據分析挑戰相連。其中第一個項目是使用TensorFlow的圖像識別應用程序，充分體現了當今數據分析中人工智能的重要性。第二個行業項目分析社交媒體趨勢，探索大數據問題和自然語言處理的人工智能方法。第三個案例研究是金融投資組合分析應用程序，讓您深入了解時間序列分析，這在當今許多數據科學應用中至關重要。第四個行業用例將帶您深入圖形算法和現代數據科學的編程力量。最後，您將深入思考數據科學的未來以及它如何利用算法和人工智能的力量。

《你將學到什麼》
- 一套精心打造的新工具，以應對您的數據分析挑戰
- 在當今幾個關鍵行業背景下，對工具集進行全面詳細的案例研究
- 通過Python和Jupyter Notebook的新工具集，提高工作效率
- 展望數據科學的未來，以及如何發展您的下一步技能

《本書適合對象》
本書適合開發人員希望彌補他們與數據科學家之間的差距。作為PixieDust的創造者，本書是熟練的數據科學家的絕佳桌面伴侶。假設您對數據解釋和可視化有一定的熟悉程度。對Python、使用Python庫以及網頁開發有一定的了解將有所幫助。

《目錄》
1. 編程和數據科學-一套新工具
2. 使用Python和Jupyter Notebook提升數據分析能力
3. 使用Python庫加速數據分析
4. 將數據分析發布到Web-PixieApp工具
5. Python和PixieDust的最佳實踐和高級概念
6. 分析研究：使用TensorFlow進行人工智能和圖像識別
7. 分析研究：使用Twitter情感分析進行NLP和大數據分析
8. 分析研究：預測-金融時間序列分析和預測
9. 分析研究：圖形算法-美國國內航班數據分析
10. 數據分析的未來和您下一步技能的發展