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Articles by Mithilesh Pradhan
44 articles
Python | Measure similarity between two sentences using cosine similarity
Natural Language Processing for finding the semantic similarity between sentences, words, or text is very common in modern use cases. Cosine similarity is a popular method that measures the cosine of the angle between two non-zero vectors using dot product formula notation. Through this article let us briefly explore cosine similarity and see its implementation using Python. What is Cosine Similarity? Cosine similarity is defined as the cosine of the angle between two vectors in space. A sentence or text can be represented as a vector based on word frequencies. The similarity between two sentences depends upon ...
Read MoreCombining IoT and Machine Learning makes our future smarter
The Internet of Things (IoT) creates networks of connected devices that collect data through sensors, while Machine Learning transforms this data into intelligent insights. Combining these technologies enables smart systems that can make autonomous decisions and adapt to changing conditions in real-time. What is IoT and Machine Learning Integration? The Internet of Things (IoT) consists of embedded devices, smart sensors, and computers that communicate through networks to collect and exchange data. These devices interact with the physical world using sensors for data collection and actuators for control operations. Machine Learning algorithms process the massive amounts of data ...
Read MoreSynsets for a word in WordNet in NLP
WordNet is a large lexical database available in the NLTK library that organizes words by their semantic relationships. It provides an interface called Synsets (synonym sets) that groups semantically similar words together, making it valuable for Natural Language Processing tasks. WordNet Structure and Synsets Animal Mammal Bird Dog Cat Eagle ...
Read MoreExploring Data Distribution
Data distribution analysis is a fundamental aspect of exploratory data analysis in data science and machine learning. Understanding how your data is distributed helps identify patterns, outliers, central tendencies, and the overall shape of your dataset. Python provides several powerful visualization tools to explore data distributions effectively. Histograms and Density Plots Histograms are the most popular graphical method for exploring data distribution. They use rectangular bars to represent the frequency of values within specific intervals called bins. A KDE (Kernel Density Estimation) plot shows the probability density function as a smooth curve. Basic Histogram Example ...
Read MoreMultilingual Google Meet Summarizer and Python Project
A Multilingual Google Meet Summarizer is a Chrome extension that automatically transcribes and summarizes Google Meet conversations in multiple languages. This tool became especially valuable during remote work periods when effective meeting documentation was crucial for productivity. In this article, we'll explore the project architecture and examine key implementation details using Python for natural language processing and summarization. Project Overview This Chrome extension captures audio from Google Meet sessions, generates transcriptions, and creates summarized versions in various languages. The system combines web technologies with machine learning for intelligent text processing. Technology Stack Frontend − ...
Read MoreImplementation of Teaching Learning Based Optimization
Teaching Learning Based Optimization (TLBO) is a population-based metaheuristic algorithm inspired by the teaching-learning process in a classroom. The algorithm mimics the interaction between a teacher and students, where knowledge is transferred through teaching and peer learning phases. What is TLBO? TLBO considers a population (class) with learners who gain knowledge through two distinct phases: Teaching Phase − The teacher shares knowledge with all learners Learning Phase − Learners interact among themselves to improve their knowledge Each learner represents a potential solution, and their "knowledge" corresponds to the fitness value of the optimization problem. ...
Read MoreLocally Weighted Linear Regression in Python
Locally Weighted Linear Regression (LOESS) is a non-parametric algorithm that adapts to local patterns in data. Unlike standard linear regression which assumes global linearity, LOESS gives more weight to nearby points when making predictions, making it suitable for non-linear data distributions. Parametric vs Non-Parametric Models Parametric Models Parametric models assume a specific functional form and have a fixed number of parameters. For example, linear regression uses the equation: b₀ + b₁x₁ + b₂x₂ = 0 Here, b₀, b₁, and b₂ are fixed coefficients that define the line's intercept and slope. Non-Parametric Models ...
Read MoreHandwritten Digit Recognition using Neural Network
Handwritten digit recognition is a fundamental task in computer vision and deep learning. It demonstrates how neural networks can classify images into multiple categories, making it an excellent introduction to multiclass image classification using convolutional neural networks. Binary vs Multiclass Image Classification Before diving into digit recognition, let's understand the classification types: Binary Image Classification In binary classification, the model predicts between two classes. For example, classifying images as either cats or dogs. Multiclass Image Classification In multiclass classification, the model predicts among more than two classes. Handwritten digit recognition is a perfect example, where we ...
Read MoreRegression Analysis and the Best Fitting Line using Python
In this tutorial, we will implement regression analysis and find the best-fitting line using Python. We'll explore linear regression concepts and demonstrate practical implementation with scikit-learn. What is Regression Analysis? Regression analysis is a statistical method for modeling relationships between variables. Linear regression specifically models the relationship between a dependent variable (target) and one or more independent variables using a linear equation. In machine learning, linear regression is a supervised algorithm that predicts continuous target values like salary, temperature, or stock prices based on input features. Linear Regression Equation The linear regression equation follows the ...
Read MoreHow to split a Dataset into Train sets and Test sets in Python?
In this tutorial, we will learn how to split a dataset into train sets and test sets using Python. This is a fundamental preprocessing step in machine learning that helps build robust models. Why Split Datasets? When creating machine learning models, we need to evaluate their performance on unseen data. Common problems include overfitting (model performs well on training data but fails on new data) and underfitting (model performs poorly on both training and new data). Splitting the dataset helps us: Train set − Used to train the model (typically 70-80% of data) Test set ...
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