Mastering Machine Learning with Python in Six Steps : a Practical Implementation Guide to Predictive Data Analytics Using Python /: a Practical Implementation Guide to Predictive Data Analytics Using Python. (2019)

• Record Type: Book
• Further Information: Note: Manohar Swamynathan.
• Other Names: Swamynathan, Manohar
• Contents: Intro; Table of Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Step 1: Getting Started in Python 3; The Best Things in Life Are Free; The Rising Star; Choosing Python 2.x or Python 3.x; Windows; OSX; Graphical Installer; Command Line Installer; Linux; From Official Website; Running Python; Key Concepts; Python Identifiers; Keywords; My First Python Program; Code Blocks; Indentations; Suites; Basic Object Types; When to Use List, Tuple, Set, or Dictionary; Comments in Python; Multiline Statements; Multiple Statements on a Single Line Basic OperatorsArithmetic Operators; Comparison or Relational Operators; Assignment Operators; Bitwise Operators; Logical Operators; Membership Operators; Identity Operators; Control Structures; Selections; Iterations; Lists; Tuples; Sets; Changing Sets in Python; Removing Items from Sets; Set Operations; Set Unions; Set Intersections; Set Difference; Set Symmetric Difference; Basic Operations; Dictionary; User-Defined Functions; Defining a Function; The Scope of Variables; Default Argument; Variable Length Arguments; Modules; File Input/Output; Opening a File; Exception Handling; Summary Chapter 2: Step 2: Introduction to Machine LearningHistory and Evolution; Artificial Intelligence Evolution; Different Forms; Statistics; Frequentist; Bayesian; Regression; Data Mining; Data Analytics; Descriptive Analytics; Diagnostic Analytics; Predictive Analytics; Prescriptive Analytics; Data Science; Statistics vs. Data Mining vs. Data Analytics vs. Data Science; Machine Learning Categories; Supervised Learning; Unsupervised Learning; Reinforcement Learning; Frameworks for Building ML Systems; Knowledge Discovery in Databases; Selection; Preprocessing; Transformation; Data Mining Interpretation / EvaluationCross-Industry Standard Process for Data Mining; Phase 1: Business Understanding; Phase 2: Data Understanding; Phase 3: Data Preparation; Phase 4: Modeling; Phase 5: Evaluation; Phase 6: Deployment; SEMMA (Sample, Explore, Modify, Model, Assess); Sample; Explore; Modify; Model; Assess; Machine Learning Python Packages; Data Analysis Packages; NumPy; Array; Creating NumPy Array; Data Types; Array Indexing; Field Access; Basic Slicing; Advanced Indexing; Array Math; Broadcasting; Pandas; Data Structures; Series; DataFrame; Reading and Writing Data Basic Statistics SummaryViewing Data; Basic Operations; Merge/Join; Join; Grouping; Pivot Tables; Matplotlib; Using Global Functions; Customizing Labels; Object-Oriented; Line Plots Using ax.plot(); Multiple Lines on the Same Axis; Multiple Lines on Different Axis; Control the Line Style and Marker Style; Line Style Reference; Marker Reference; Colormaps Reference; Bar Plots Using ax.bar(); Horizontal Bar Charts Using ax.barh(); Side by Side Bar Chart; Stacked Bar Example Code; Pie Chart Using ax.pie(); Example Code for Grid Creation; Plotting Defaults; Machine Learning Core Libraries
• Edition: 2nd ed
• Publisher Details: Berkeley, CA : Apress L.P
• Publication Date: 2019
• Extent: 1 online resource (469 pages)
• Subjects: 005.13/3; Machine learning; Python (Computer program language); Machine learning; Python (Computer program language); Electronic books
• Languages: English
• ISBNs: 9781484249475
• Related ISBNs: 148424947X; 9781484249468
• Notes: Note: Print version record.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.