Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
Higher-Order Functions: Lambda
Graph Chatbot
Related lectures (31)
Python Basics: Functions and Lists
Introduces Python basics, functions, lists, and lambda functions for concise coding.
Functional Programming in Python
Covers functional programming concepts in Python, showcasing filtering lists based on specific criteria.
Functional Programming: Concepts and Implementation
Covers the concepts and implementation of functional programming in Scala, emphasizing functions, immutable data, and data abstraction.
Encoding Recursion as Self-Application
Explores lambda calculus, higher-order functions, and recursive function encoding.
Programming Concepts: Functions, Inheritance, Code Optimization
Covers advanced programming concepts like higher-order functions and inheritance.
Higher-Order Functions
Covers higher-order functions, function types, and anonymous functions in programming.
Recursive Functions: Examples and Applications
Explores recursive functions, including factorials and Fibonacci sequences, and their scope and namespaces.
Scopes and Lambdas: Data Science with Python
Covers scopes, lambdas, and pandas in data science with Python, including nested declarations, scoping, assignments, and pandas manipulation.
Class hierarchies: pattern matching
Covers class hierarchies, pattern matching, function values, and function calls in Scala.
Python Basics: Functions and Types
Covers Python basics, including data types, loops, functions, classes, and GUI creation.
Functions: Python Basics
Covers the basics of functions in Python, including their definition, purpose, and usage.
Avoiding Variable Capture
Explores variable capture in higher-order functions and the importance of variable renaming.
Combinatorial Search: For-Expressions
Explores the use of for-expressions in Scala to simplify computations and solve problems like combinatorial search and N-Queens.
Church Numerals and Conditionals
Explores Church numerals and encoding conditionals in lambda calculus.
General Introduction to Data Science
Offers a comprehensive introduction to Data Science, covering Python, Numpy, Pandas, Matplotlib, and Scikit-learn, with a focus on practical exercises and collaborative work.
Python Functions: Basics and Arguments
Covers the basics of writing functions in Python and working with function arguments.
Polymorphism and Proofs
Covers parametric polymorphism, lists construction, tuples, generic methods, merge sort, and proving program properties.
Finding Fixed Points: Iterative Methods for Convergence
Covers iterative methods for finding fixed points of functions, focusing on square root calculations and the power of functions as return values.
Functions in Python
Introduces functions in Python, covering predefined and user-defined functions, formal and effective parameters, and the importance of docstrings.
Functions: Reusability and Error Reduction
Covers functions in C programming, emphasizing reusability and error reduction through proper function structure.
Previous
Page 1 of 2
Next