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36 notes
note06 thèmes

Classification with a Neural Network

Neural networks are advanced computational models that mimic the human brain's structure, enabling them to capture and model complex, non-linear relationships between inputs and outputs. The

#basic#calculus#machine-learning
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note05 thèmes

`DataFrame` data structure

The DataFrame data structure is the heart of the Panda's library. It's a primary object used in data analysis and cleaning tasks. Conceptually, a DataFrame is a two-dimensional series object

#infotech#packages#pandas
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note05 thèmes

`DataFrame` Indexing and Loading

Introduction to CSV Files

#infotech#packages#pandas
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note05 thèmes

`Series` Data Structure

A Series in pandas is a one-dimensional array-like object that can hold various data types, similar to a list in Python, but with additional features. It combines elements of lists and dicti

#infotech#packages#pandas
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note05 thèmes

Activity Selection

The Activity Selection problem is a classic example of a greedy algorithm application. It is concerned with selecting the maximum number of activities that don't overlap in time from a given

#activity-selection#algorithms#greedy-algorithms
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note05 thèmes

Bellman-Ford Algorithm

The Bellman-Ford algorithm is a graph-searching algorithm that calculates the shortest paths from a single source vertex to all other vertices in a weighted graph. It is particularly useful

#algorithms#bellman-ford-algorithm#graph-algorithms
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note05 thèmes

Binary Search

Binary search is a highly efficient searching algorithm used to find the position of a target value within a sorted array. This algorithm operates on the divide and conquer principle, which

#algorithms#binary-search#infotech
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note05 thèmes

Breadth-first search (BFS)

Breadth-first search BFS is a widely used algorithm for traversing or searching tree and graph data structures. It starts at a selected node often referred to as the 'root' in the context of

#algorithms#breadth-first-search#infotech
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note05 thèmes

Bubble Sort

Bubble Sort is one of the simplest sorting algorithms in computer science. It repeatedly steps through the list to be sorted, compares adjacent elements, and swaps them if they are in the wr

#algorithms#bubble-sort#infotech
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note05 thèmes

Data Cleaning with Pandas

In this lecture, we covered a basic data cleaning process using pandas. We focused on cleaning a dataset containing a list of US presidents from Wikipedia. The key operations included import

#infotech#packages#pandas
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note05 thèmes

Date Functionality

In today's lecture, we explored time series and date functionality in pandas. Manipulating dates and times in pandas is highly flexible, enabling us to conduct advanced analysis such as time

#infotech#packages#pandas
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note05 thèmes

Depth-First Search (DFS)

Depth-First Search DFS is a fundamental algorithm used in graph theory to traverse or search through the nodes of a graph in a systematic manner. DFS explores as deep as possible along each

#algorithms#depth-first-search#infotech
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note05 thèmes

Dijkstra's Algorithm

Dijkstra's algorithm is a graph search algorithm that finds the shortest paths from a single source node to all other nodes in a weighted graph with non-negative edge weights. It was conceiv

#algorithms#dijkstra's-algorithm#graph-algorithms
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note05 thèmes

Errors and Exceptions

The Try-Except Construct

#infotech#intermediate#programming-languages
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note05 thèmes

Fibonacci Series

The Fibonacci series is a sequence of numbers where each number is the sum of the two preceding ones, usually starting with 0 and 1. Mathematically, it is defined as:

#algorithms#dynamic-programming#fibonacci-series
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note05 thèmes

Floyd-Warshall Algorithm

The Floyd-Warshall Algorithm is a dynamic programming method used to find the shortest paths between all pairs of nodes in a weighted graph. This algorithm can handle both directed and undir

#algorithms#floyd-warshall-algorithm#graph-algorithms
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note05 thèmes

Fractional Knapsack Problem

The Fractional Knapsack Problem is a variant of the knapsack problem where it's permissible to take fractional parts of items rather than having to make a binary choice for each item all or

#algorithms#fractional-knapsack-problem#greedy-algorithms
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note05 thèmes

Grouping Data

Grouping data is an essential task for data analysis, allowing us to understand and manipulate data at a group level. Pandas provides the groupby function to facilitate this, implementing th

#infotech#packages#pandas
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note05 thèmes

Heap Sort

Heap Sort is a comparison-based sorting algorithm that uses a binary heap data structure to efficiently sort elements. It's particularly effective for data sets stored in random access struc

#algorithms#heap-sort#infotech
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note05 thèmes

Huffman Coding

Huffman Coding is a widely used method for data compression that involves creating variable-length codes for input characters, with the lengths based on the frequencies of the characters. It

#algorithms#greedy-algorithms#huffman-coding
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note05 thèmes

Idioms

In Python programming, certain idioms are considered more appropriate and efficient. Pandas, a sub-language within Python, has its own idioms, often referred to as "pandorable." These idioms

#infotech#packages#pandas
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note05 thèmes

Indexing `DataFrame`

In pandas, both Series and DataFrame objects can have indices applied to them. An index serves as a row-level label, corresponding to axis zero. Indices can be autogenerated or explicitly se

#infotech#packages#pandas
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note05 thèmes

Insertion Sort

Insertion Sort is a fundamental comparison-based sorting algorithm that mirrors the way you might sort playing cards in your hand. By building a sorted array one element at a time, it offers

#algorithms#infotech#insertion-sort
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note05 thèmes

Job Sequencing Problem

The Job Sequencing Problem is a classic problem in computer science, often solved using greedy algorithms. The problem involves scheduling jobs to maximize profit when each job has a deadlin

#algorithms#greedy-algorithms#infotech
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note05 thèmes

Knapsack Problem

The Knapsack Problem is a classic optimization problem that can be efficiently solved using dynamic programming. The goal is to choose a subset of items with maximum total value, subject to

#algorithms#dynamic-programming#infotech
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note05 thèmes

Kruskal's algorithm

Kruskal's algorithm is a popular method used to find the minimum spanning tree MST for a connected, weighted, undirected graph. The goal of the algorithm is to find a subset of the graph's e

#algorithms#graph-algorithms#infotech
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note05 thèmes

Linear Search

Linear search, also known as sequential search, is a fundamental algorithm used to find a specific element within a list. It operates by starting at the beginning of the list and examining e

#algorithms#infotech#linear-search
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note05 thèmes

Log Loss in Machine Learning

Machine learning often involves optimization problems that aim to minimize or maximize a particular function, known as a loss function. Two of the most common loss functions are square loss

#basic#calculus#machine-learning
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note05 thèmes

Longest Common Subsequence

The Longest Common Subsequence LCS problem is a classic computer science problem used to find the longest subsequence common to all sequences in a set of sequences often just two sequences .

#algorithms#dynamic-programming#infotech
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note05 thèmes

Merge Sort

Merge Sort is an efficient, general-purpose, comparison-based sorting algorithm. It follows the divide and conquer paradigm, which involves breaking a problem into smaller subproblems, solvi

#algorithms#infotech#merge-sort
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note05 thèmes

Merging DataFrames

Relational Theory Concepts

#infotech#packages#pandas
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note05 thèmes

Minimum Spanning Tree (MST)

In graph theory, a Minimum Spanning Tree MST for a weighted graph is a spanning tree with the minimum weight among all the spanning trees. It connects all the vertices together without any c

#algorithms#greedy-algorithms#infotech
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note05 thèmes

Missing Values

Missing values are common in data cleaning activities and can occur for various reasons. Understanding the nature and handling of missing data is crucial for accurate data analysis.

#infotech#packages#pandas
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note05 thèmes

Ordinary Least Squares

Linear models aim to predict a target value as a linear combination of input features. Commonly represented with:

#infotech#linear-models#machine-learning
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note05 thèmes

Other Test Concepts

Black Box vs. White Box Testing

#infotech#intermediate#programming-languages
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note05 thèmes

Pandas

Official Website

#infotech#packages#pandas
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