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Articles by Kalyan Mishra
Page 2 of 6
Finding the Word Analogy from given words using Word2Vec embeddings
In this article, we will learn about a machine learning program that can find word analogies from provided words. For example: "Apple : fruit :: car : vehicle". In this analogy, "apple" and "car" are the two things being compared. "Fruit" and "vehicle" are the categories that these items belong to. The analogy states that apple is a type of fruit, just as car is a type of vehicle. While the human brain can easily identify such patterns, training a machine to perform the same task requires a very large amount of data. We will use the Word2Vec ...
Read MoreUnderstanding the Interpretations of Histograms
Histograms are fundamental tools for visualizing data distributions and understanding patterns in datasets. This article explores different types of histograms and their interpretations using Python's matplotlib library. What is a Histogram? A histogram provides a visual representation of numerical data by displaying it as a bar chart. It helps visualize distributions and patterns in datasets where the x-axis represents ranges of values (bins) and the y-axis shows the frequency or count of data points falling within each range. Applications of Histograms Data Distribution Analysis Histograms help analyze data distribution characteristics including shape, spread, skewness, and ...
Read MoreTypes Of Activation Functions in ANN
This article explores Artificial Neural Networks (ANN) and the various activation functions that enable them to learn complex patterns. We'll examine how different activation functions transform inputs and their specific use cases in neural network architectures. What is an Artificial Neural Network (ANN)? An Artificial Neural Network (ANN) is a machine learning model inspired by the human brain's structure. It consists of interconnected nodes (neurons) that process and transmit information through weighted connections. These networks learn by adjusting weights during training to produce desired outputs. ANN Architecture: Three Essential Layers Input Layer The input layer ...
Read MoreImage Classification using Google\'s Teachable Machine
In this article, you will learn about machine learning, image classification, and how to use Google's Teachable Machine to train models without writing code. Machine Learning Machine learning is a subset of artificial intelligence (AI) that enables computers to learn and make decisions from data without explicit programming. This approach allows machines to identify patterns, make predictions, and improve performance over time based on the provided data. Image Classification Image classification is a machine learning process that assigns labels to images based on their content. This technique is fundamental in computer vision and is used for ...
Read MoreRole of Text to text Transfer Transformer in Data Augmentation
In this article, we will learn about the role of Text-to-Text Transfer Transformer (T5) in data augmentation and how this technique can improve NLP model performance through synthetic data generation. Natural Language Processing has seen rapid advancement in data augmentation techniques. Data augmentation improves NLP model performance by creating additional training examples. Among various techniques available, Text-to-Text Transfer Transformer (T5) stands out as a unified approach that can perform multiple NLP tasks using a consistent text-to-text format. What is Data Augmentation? Data augmentation is a technique used to artificially expand training datasets by creating modified versions of ...
Read MorePython - Uneven Sized Matrix Column Product
In this article we will learn about various methods using which we can find products of uneven size matrix columns. Working with matrices is very common in fields like data analysis and machine learning, so there can be situations where we have to find the matrix column product which can be a challenging task. Let's see some examples for finding the uneven size matrix column product − Method 1: Using a Simple Loop In this method we will use the concept of simple nested loop and we will iterate through the matrix columns and compute their products. ...
Read MoreFinding the Summation of Random Numbers using Python
In this article, we will learn different methods to find the summation of random numbers using Python. Whether you need to generate random numbers for testing, simulations, or statistical analysis, these approaches will help you calculate their sum efficiently. Let's explore various methods to generate random numbers and calculate their summation ? Using Simple Loop This method generates random numbers using a loop and stores them in a list before calculating the sum ? import random n = 10 rand_nums = [] for _ in range(n): rand_nums.append(random.randint(1, 100)) total ...
Read MoreQueue.LIFOQueue vs Collections.Deque in Python
In this article we will learn about Queue.LIFOQueue vs Collections.Deque in Python programming language. When we need to manage our data using the last in first out method, we can use these data structures. But to choose one of them we need to know about their functionalities and characteristics. Queue.LIFOQueue This class is part of the queue module. It works as a stack data structure and is thread-safe, meaning we can communicate between different threads simultaneously. Here are some key specifications: Stack-based − LIFOQueue behaves like a stack data structure where the item inserted last will ...
Read MorePython - Replace sublist with others in list
Replacing a sublist (portion of a list) with another list is a common operation in Python. This article explores multiple approaches to replace elements at specific index ranges with new values. Let's understand the problem with an example ? original_list = [1, 2, 3, 4, 5, 6] new_items = [7, 8, 9] # Replace elements from index 2 to 5 (exclusive) with new_items # Result should be: [1, 2, 7, 8, 9, 6] Using List Slicing (Recommended) The simplest and most Pythonic approach uses slice assignment to replace a sublist ? ...
Read MorePython - Replace rear word in String
In this article, we will learn how to replace the rear (last) word in a string with any other given word. This is a common string manipulation task in Python programming. Let's understand this with an example ? original_string = "This cat is running very Fast" # We want to replace "Fast" with "Slow" # Result: "This cat is running very Slow" Method 1: Using split() and join() The most straightforward approach is to split the string into words, replace the last word, and join them back ? def replace_rear(text, new_word): ...
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