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Matplotlib: Overview
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Related lectures (53)
Data Science: Python for Engineers - Part II
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Explores data wrangling, numerical data handling, and scientific visualization using Python for engineers.
Introduction to Python Programming
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Introduces Python programming basics using Anaconda and JupyterLab, with practical exercises on syntax and libraries.
Programming for Engineers: Advanced MATLAB Techniques
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Explores advanced MATLAB techniques, emphasizing vectorization, 'find' function, and plot manipulation.
Nonlinear Equation Resolution: Introduction to Bisection Method
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Introduces the bisection method for resolving nonlinear equations using numerical techniques and Python programming.
Graphs in Deep Learning: Applications and Techniques
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Explores the role of graphs in deep learning, focusing on their structure, applications, and techniques for processing graph data.
Pseudorandomness: Theory and Applications
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Explores pseudorandomness theory, AI challenges, pseudo-random graphs, random walks, and matrix properties.
Iterated Integrals: Order and Domains
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Explores iterated integrals, order, domains, and symmetrical roles of variables in 2D space.
Data Visualization Techniques: Applications and Principles
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Discusses data visualization techniques, emphasizing their applications and principles for effective communication of complex information.
Sparsest Cut: Bourgain's Theorem
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Explores Bourgain's theorem on sparsest cut in graphs, emphasizing semimetrics and cut optimization.
Python Programming: Immutable and Mutable Objects
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Explains the differences between mutable and immutable objects in Python, focusing on lists, sets, and their behaviors.
Introduction to Programming: Basics of Python
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Covers the basics of programming in Python, focusing on practical skills and hands-on exercises.
Uniform Acceleration: Equations and Interpretation
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Covers the concept of uniform acceleration and its equations.
Functions and Control Structures in Python
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Introduces functions and control structures in Python, emphasizing their importance for code organization and reusability.
Introduction to Matplotlib
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Introduces matplotlib for 2D graphic representation and data visualization with numpy.
Programming for Engineers
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Covers programming concepts using MATLAB, C, and LabVIEW for engineering projects, including a billiards game analysis.
Distributed Information Systems: Overview and Course Information
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Covers key concepts of Distributed Information Systems and course logistics.
Data Science Visualization with Pandas
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Covers data manipulation and exploration using Python with a focus on visualization techniques.
Data Visualization & Storytelling
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Delves into data physicalization, expressiveness, feminist visualization, and the balance between exploration and explanation in data visualization.
Algorithmic Foundations for Systems Certification
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Explores challenges in designing systems with untrustworthy components, focusing on verification, control, and interaction in unreliable systems.
Digital History and Digitized Press
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Delves into the 'digital turn' in history, examining historical research using digitized newspapers and exploring text reuse, word embeddings, and data visualization.
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