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Python for Data Science: Data analysis and Deep learning with Python coding and programming

Book information

Language
english
Format
PDF
Filesize
1 MB (1217902 bytes)
Pages
\73
Time added
2020-08-14 22:45:04

Description

Introduction: Chapter 1: What is Data Analysis? Chapter 2: The Basics of the Python Language The Statements The Python Operators The Keywords Working with Comments The Python Class How to Name Your Identifiers Python Functions Chapter 3: Using Pandas Pandas Chapter 4: Working with Python for Data Science Why Python Is Important? What Is Python? Python's Position in Data Science Data Cleaning Data Visualization Feature Extraction Model Building Python Installation Installation Under Windows Conda Spyder Installation Under MAC Installation Under Linux Install Python Chapter 5: Indexing and Selecting Arrays Conditional selection NumPy Array Operations Array – Array Operations Array – Scalar operations Chapter 6: K-Nearest Neighbors Algorithm Splitting the Dataset Feature Scaling Training the Algorithm Evaluating the Accuracy K Means Clustering Data Preparation Visualizing the Data Creating Clusters Chapter 7: Big Data The Challenge Applications in the Real World Chapter 8: Reading Data in your Script Reading data from a file Dealing with corrupt data Chapter 9: The Basics of Machine Learning The Learning Framework PAC Learning Strategies The Generalization Models Chapter 10: Using Scikit-Learn Uses of Scikit-Learn Representing Data in Scikit-Learn Tabular Data Features Matrix Target Arrays Understanding the API Conclusion:

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