| 청구기호 |
QA76.73.P98 |
| 형태사항 |
1 online resource
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| 언어 |
English |
| 내용 |
Cover; Title Page; Copyright; About the Author; About the Technical Editor; Credits; Acknowledgments; Contents at a glance; Contents; Introduction; Chapter 1 Introduction to Machine Learning; What Is Machine Learning?; What Problems Will Machine Learning Be Solving in This Book?; Classification; Regression; Clustering; Types of Machine Learning Algorithms; Supervised Learning; Unsupervised Learning; Getting the Tools; Obtaining Anaconda; Installing Anaconda; Running Jupyter Notebook for Mac; Running Jupyter Notebook for Windows; Creating a New Notebook; Naming the Notebook
Adding and Removing CellsRunning a Cell; Restarting the Kernel; Exporting Your Notebook; Getting Help; Summary; Chapter 2 Extending Python Using NumPy; What Is NumPy?; Creating NumPy Arrays; Array Indexing; Boolean Indexing; Slicing Arrays; NumPy Slice Is a Reference; Reshaping Arrays; Array Math; Dot Product; Matrix; Cumulative Sum; NumPy Sorting; Array Assignment; Copying by Reference; Copying by View (Shallow Copy); Copying by Value (Deep Copy); Summary; Chapter 3 Manipulating Tabular Data Using Pandas; What Is Pandas?; Pandas Series; Creating a Series Using a Specified Index
Accessing Elements in a SeriesSpecifying a Datetime Range as the Index of a Series; Date Ranges; Pandas DataFrame; Creating a DataFrame; Specifying the Index in a DataFrame; Generating Descriptive Statistics on the DataFrame; Extracting from DataFrames; Selecting the First and Last Five Rows; Selecting a Specific Column in a DataFrame; Slicing Based on Row Number; Slicing Based on Row and Column Numbers; Slicing Based on Labels; Selecting a Single Cell in a DataFrame; Selecting Based on Cell Value; Transforming DataFrames; Checking to See If a Result Is a DataFrame or Series
Sorting Data in a DataFrameSorting by Index; Sorting by Value; Applying Functions to a DataFrame; Adding and Removing Rows and Columns in a DataFrame; Adding a Column; Removing Rows; Removing Columns; Generating a Crosstab; Summary; Chapter 4 Data Visualization Using matplotlib; What Is matplotlib?; Plotting Line Charts; Adding Title and Labels; Styling; Plotting Multiple Lines in the Same Chart; Adding a Legend; Plotting Bar Charts; Adding Another Bar to the Chart; Changing the Tick Marks; Plotting Pie Charts; Exploding the Slices; Displaying Custom Colors; Rotating the Pie Chart
Displaying a LegendSaving the Chart; Plotting Scatter Plots; Combining Plots; Subplots; Plotting Using Seaborn; Displaying Categorical Plots; Displaying Lmplots; Displaying Swarmplots; Summary; Chapter 5 Getting Started with Scikit-learn for Machine Learning; Introduction to Scikit-learn; Getting Datasets; Using the Scikit-learn Dataset; Using the Kaggle Dataset; Using the UCI (University of California, Irvine) Machine Learning Repository; Generating Your Own Dataset; Linearly Distributed Dataset; Clustered Dataset; Clustered Dataset Distributed in Circular Fashion
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| 주제 |
Machine learning.
Python (Computer program language)
COMPUTERS --Programming Languages --Python. --bisacsh
Machine learning. --fast --(OCoLC)fst01004795
Python (Computer program language) --fast --(OCoLC)fst01084736
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| 보유판 및 특별호 저록 |
Print version: Lee, Wei-Meng. Python machine learning. Indianapolis, IN : Wiley, 2019 1119545633 9781119545637 , 1042350760
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| ISBN |
9781119545675, 1119545676, 9781119545699, 1119545692, 9781119557500, 111955750X, 9781119545637
, 1119545633
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| QR CODE |
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