Data Analysis Foundations with Python. (Record no. 15244)
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| fixed length control field | 03586nam a2200265uu 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250710181508.0 |
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| fixed length control field | 250616s||||||||||||||||o||||||||||| |d |
| 024 80 - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 9781836209065 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | PACKT |
| Transcribing agency | PACKT |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | en |
| 044 ## - COUNTRY OF PUBLISHING/PRODUCING ENTITY CODE | |
| MARC country code | GB |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Cuantum Technologies LLC |
| Relator term | author. |
| 245 00 - TITLE STATEMENT | |
| Title | Data Analysis Foundations with Python. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | GB: |
| Name of publisher, distributor, etc. | Packt, |
| Date of publication, distribution, etc. | 2024-06-12. |
| 263 ## - PROJECTED PUBLICATION DATE | |
| Projected publication date | 2024-06-12 |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | GB: |
| Name of producer, publisher, distributor, manufacturer | Packt, |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 551. |
| 377 ## - ASSOCIATED LANGUAGE | |
| Language code | en |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | <p><b>Dive into data analysis with Python, starting from the basics to advanced techniques. This course covers Python programming, data manipulation with Pandas, data visualization, exploratory data analysis, and machine learning.</b></p><h4>Key Features</h4><ul><li>From Python basics to advanced data analysis techniques.</li><li>Apply your skills to practical scenarios through real-world case studies.</li><li>Detailed projects and quizzes to help gain the necessary skills.</li></ul><h4>Book Description</h4>Embark on a comprehensive journey through data analysis with Python. Begin with an introduction to data analysis and Python, setting a strong foundation before delving into Python programming basics. Learn to set up your data analysis environment, ensuring you have the necessary tools and libraries at your fingertips. As you progress, gain proficiency in NumPy for numerical operations and Pandas for data manipulation, mastering the skills to handle and transform data efficiently.<br/>Proceed to data visualization with Matplotlib and Seaborn, where you'll create insightful visualizations to uncover patterns and trends. Understand the core principles of exploratory data analysis (EDA) and data preprocessing, preparing your data for robust analysis. Explore probability theory and hypothesis testing to make data-driven conclusions and get introduced to the fundamentals of machine learning. Delve into supervised and unsupervised learning techniques, laying the groundwork for predictive modeling.<br/>To solidify your knowledge, engage with two practical case studies: sales data analysis and social media sentiment analysis. These real-world applications will demonstrate best practices and provide valuable tips for your data analysis projects.<h4>What you will learn</h4><ul><li>Develop a strong foundation in Python for data analysis.</li><li>Manipulate and analyze data using NumPy and Pandas.</li><li>Create insightful data visualizations with Matplotlib and Seaborn.</li><li>Understand and apply probability theory and hypothesis testing.</li><li>Implement supervised and unsupervised machine learning algorithms.</li><li>Execute real-world data analysis projects with confidence.</li></ul><h4>Who this book is for</h4>This course adopts a hands-on approach, seamlessly blending theoretical lessons with practical exercises and real-world case studies. Practical exercises are designed to apply theoretical knowledge, providing learners with the opportunity to experiment and learn through doing. Real-world applications and examples are integrated throughout the course to contextualize concepts, making the learning process engaging, relevant, and effective. By the end of the course, students will have a thorough understanding of the subject matter and the ability to apply their knowledge in practical scenarios. |
| 538 ## - SYSTEM DETAILS NOTE | |
| System details note | Data in extended ASCII character set. |
| 538 ## - SYSTEM DETAILS NOTE | |
| System details note | Mode of access: Internet. |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | PACKT |
| 773 0# - HOST ITEM ENTRY | |
| Title | Data Analysis Foundations with Python |
| Place, publisher, and date of publication | GB,Packt,2024-06-12 |
| Physical description | 551 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://learning.packt.com/product/473588">https://learning.packt.com/product/473588</a> |
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