Simple Introduction to Python
portes grátis
Simple Introduction to Python
Lynch, Stephen
Taylor & Francis Ltd
06/2024
92
Dura
9781032751672
Pré-lançamento - envio 15 a 20 dias após a sua edição
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1. Python as a Powerful Calculator. 1.1. BODMAS. 1.2. Fractions: Symbolic Computation. 1.3. Powers (Exponentiation) and Roots. 1.4. The Math Library (Module) Chapter. 2. Simple Programming With Python. 2.1. Lists, Tuples, Sets and Dictionaries. 2.2. Defining Functions (Programming). 2.3. For and While Loops. 2.4. Conditional Statements, If, Elif, Else. 3. The Turtle Library. 3.1. The Cantor Set Fractal. 3.2. The Koch Snowflake. 3.3. A Bifurcating Tree. 3.4. The Sierpinski Triangle. 4. NumPy and MatPlotLib. 4.1. Numerical Python (Numpy). 4.2. MatPlotLib. 4.3. Scatter Plots. 4.4. Surface Plots. 5. Google Colab, SymPy and GitHub. 5.1. Google Colab. 5.2. Formatting Notebooks. 5.3. Symbolic Python (Sympy). 5.4. GitHub. 6. Python for Mathematics. 6.1. Basic Algebra. 6.2. Solving Equations. 6.3. Functions (Mathematics). 6.4. Differentiation and Integration (Calculus). 7. Introduction to Cryptography. 7.1. The Caesar Cipher. 7.2. The XOR Cipher. 7.3. The Rivest-Shamir-Adleman (RSA) Cryptosystem. 7.4. Simple RSA Algorithm Example. 8. An Introduction to Artificial Intelligence. 8.1. Artificial Neural Networks. 8.2. The And/Or and XOR Gate Anns. 8.3. The Backpropagation Algorithm. 8.4. Boston Housing Data. 9. An Introduction to Data Science. 9.1. Introduction to Pandas. 9.2. Load, Clean and Preprocess the Data. 9.3. Exploring the Data. 9.4. Violin, Scatter and Hexagonal Bin Plots. 10. An Introduction to Object Oriented Programming. 10.1. Classes and Objects. 10.2. Encapsulation. 10.3. Inheritance. 10.4. Polymorphism.
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programming language;jupyter;scientific computing;quantitative sciences;coding;data science
1. Python as a Powerful Calculator. 1.1. BODMAS. 1.2. Fractions: Symbolic Computation. 1.3. Powers (Exponentiation) and Roots. 1.4. The Math Library (Module) Chapter. 2. Simple Programming With Python. 2.1. Lists, Tuples, Sets and Dictionaries. 2.2. Defining Functions (Programming). 2.3. For and While Loops. 2.4. Conditional Statements, If, Elif, Else. 3. The Turtle Library. 3.1. The Cantor Set Fractal. 3.2. The Koch Snowflake. 3.3. A Bifurcating Tree. 3.4. The Sierpinski Triangle. 4. NumPy and MatPlotLib. 4.1. Numerical Python (Numpy). 4.2. MatPlotLib. 4.3. Scatter Plots. 4.4. Surface Plots. 5. Google Colab, SymPy and GitHub. 5.1. Google Colab. 5.2. Formatting Notebooks. 5.3. Symbolic Python (Sympy). 5.4. GitHub. 6. Python for Mathematics. 6.1. Basic Algebra. 6.2. Solving Equations. 6.3. Functions (Mathematics). 6.4. Differentiation and Integration (Calculus). 7. Introduction to Cryptography. 7.1. The Caesar Cipher. 7.2. The XOR Cipher. 7.3. The Rivest-Shamir-Adleman (RSA) Cryptosystem. 7.4. Simple RSA Algorithm Example. 8. An Introduction to Artificial Intelligence. 8.1. Artificial Neural Networks. 8.2. The And/Or and XOR Gate Anns. 8.3. The Backpropagation Algorithm. 8.4. Boston Housing Data. 9. An Introduction to Data Science. 9.1. Introduction to Pandas. 9.2. Load, Clean and Preprocess the Data. 9.3. Exploring the Data. 9.4. Violin, Scatter and Hexagonal Bin Plots. 10. An Introduction to Object Oriented Programming. 10.1. Classes and Objects. 10.2. Encapsulation. 10.3. Inheritance. 10.4. Polymorphism.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
