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The Statistics and Calculus with Python Workshop
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Appendix
Areyoulookingtostartdevelopingartificialintelligenceapplications?Doyouneedarefresheronkeymathematicalconcepts?Fullofengagingpracticalexercises,TheStatisticsandCalculuswithPythonWorkshopwillshowyouhowtoapplyyourunderstandingofadvancedmathematicsinthecontextofPython.Thebookbeginsbygivingyouahigh-leveloverviewofthelibrariesyou'llusewhileperformingstatisticswithPython.Asyouprogress,you'llperformvariousmathematicaltasksusingthePythonprogramminglanguage,suchassolvingalgebraicfunctionswithPythonstartingwithbasicfunctions,andthenworkingthroughtransformationsandsolvingequations.Laterchaptersinthebookwillcoverstatisticsandcalculusconceptsandhowtousethemtosolveproblemsandgainusefulinsights.Finally,you'llstudydifferentialequationswithanemphasisonnumericalmethodsandlearnaboutalgorithmsthatdirectlycalculatevaluesoffunctions.Bytheendofthisbook,you’llhavelearnedhowtoapplyessentialstatisticsandcalculusconceptstodeveloprobustPythonapplicationsthatsolvebusinesschallenges.
目錄(90章)
倒序
- 封面
- 版權信息
- Preface
- 1. Fundamentals of Python
- Introduction
- Control Flow Methods
- Data Structures
- Functions and Algorithms
- Testing Debugging and Version Control
- Summary
- 2. Python's Main Tools for Statistics
- Introduction
- Scientific Computing and NumPy Basics
- Working with Tabular Data in pandas
- Data Visualization with Matplotlib and Seaborn
- Summary
- 3. Python's Statistical Toolbox
- Introduction
- An Overview of Statistics
- Types of Data in Statistics
- Descriptive Statistics
- Inferential Statistics
- Python's Other Statistics Tools
- Summary
- 4. Functions and Algebra with Python
- Introduction
- Functions
- Function Transformations
- Equations
- Systems of Equations
- Summary
- 5. More Mathematics with Python
- Introduction
- Sequences and Series
- Trigonometry
- Vectors
- Complex Numbers
- Summary
- 6. Matrices and Markov Chains with Python
- Introduction
- Matrix Operations on a Single Matrix
- Operations on Multiple Matrices
- Solving Linear Equations Using Matrices
- Transition Matrix and Markov Chains
- Summary
- 7. Doing Basic Statistics with Python
- Introduction
- Data Preparation
- Calculating and Using Descriptive Statistics
- Exploratory Data Analysis
- Summary
- 8. Foundational Probability Concepts and Their Applications
- Introduction
- Randomness Probability and Random Variables
- Discrete Random Variables
- Continuous Random Variables
- Summary
- 9. Intermediate Statistics with Python
- Introduction
- Law of Large Numbers
- Central Limit Theorem
- Confidence Intervals
- Hypothesis Testing
- Summary
- 10. Foundational Calculus with Python
- Introduction
- Writing the Derivative Function
- Calculating Integrals
- Using Trapezoids
- Using Integrals to Solve Applied Problems
- Using Derivatives to Solve Optimization Problems
- Summary
- 11. More Calculus with Python
- Introduction
- Length of a Curve
- Length of a Spiral
- Area of a Surface
- Infinite Series
- Summary
- 12. Intermediate Calculus with Python
- Introduction
- Differential Equations
- Interest Calculations
- Population Growth
- Half-Life of Radioactive Materials
- Newton's Law of Cooling
- Mixture Problems
- Euler's Method
- Summary
- Appendix 更新時間：2021-06-11 18:40:58
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