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An optical or visual phenomenon that creates the perception of distortion, movement or any other type of fascinating visual effect by using back and white patterns is referred to as back and white optical illusion. These back and white patterns utilize the way our eyes and brain process the visual information and create an illusion to mislead our perception. The back and white optical illusions use various black and white patterns, shapes, and lines arranged in a specific style. These arrangements are made such that they can create illusion of movement, distortion, depth, and more. In this article, we will ... Read More
PostgreSQL is a popular open−source relational database management system known for its robustness, scalability, and advanced features. Python provides excellent support for interacting with PostgreSQL databases, allowing developers to seamlessly connect and execute SQL queries. In this article, we will explore the step−by−step process of connecting to a PostgreSQL database from Python, running SQL queries, and retrieving results. We will provide code examples, explanations, and sample outputs to help you master this essential skill. In this article, we will learn how to connect and run SQL queries to a PostgreSQL database from Python. Step 1: Install the psycopg2 module The ... Read More
Any dataset used in Machine Learning algorithms may have a number of dimensions. However, not all of them contribute to giving an efficient output and simply cause the ML Model to perform poorly because of the increased size and complexity. Thus, it becomes important to eliminate such features from the dataset. To do this, we use a dimension reduction algorithm called PCA. PCA or Principal Component Analysis helps in removing those dimensions from the dataset that do not help in optimizing the results; thereby creating a smaller and simpler dataset with most of the original and useful information. PCA is ... Read More
Pandas is a Python library that is used for data analysis and manipulation. It provides a number of functions for cleaning and formatting data. In this article, we will learn how to clean string data in a given Pandas DataFrame. We will cover the following topics: Removing leading and trailing spaces Replacing special characters Converting to lowercase Removing duplicate values Splitting strings into columns Merging columns Validating data Removing Leading and Trailing Spaces The strip() method can be used to remove leading and trailing spaces from a string. For example, the following code will remove the leading ... Read More
Recommendation system is a tool in python that suggests items or content to users based on their preferences and past behaviors. This technology utilizes algorithms to predict users' future preferences, thereby providing them with the most relevant content. The scope of this system is vast, with widespread use in various industries such as e-commerce, streaming services, and social media. Products, movies, music, books, and more can all be recommended through these systems. The provision of personalized recommendations not only helps foster customer engagement and loyalty but can also boost sales. Types of Recommendation Systems Content-based recommendation systems These operate on ... Read More
Clustering is a fundamental unsupervised learning technique that aims to discover patterns or groupings in unlabeled data. It plays a crucial role in various domains such as data mining, pattern recognition, and customer segmentation. However, once clustering algorithms are applied, it becomes essential to evaluate their performance and assess the quality of the resulting clusters. Clustering performance evaluation is a critical step in understanding the effectiveness and reliability of clustering algorithms. It involves quantifying the quality of the obtained clusters and providing insights into their consistency and separability. By evaluating clustering results, practitioners can make informed decisions about algorithm selection, ... Read More
"Artificial intelligence" (AI) is a branch of computer science that tries to give computers the ability to comprehend spoken and written words similar to human beings which is a field of "natural language processing" (NLP). Computational linguistics combines a variety of technologies, including deep learning, machine learning, and statistics. Combining these technologies enables computers to completely "understand" the meaning of texts and speech, including the speaker's or writer's intention and sentiment, and to interpret human language as text and audio data. Why is it Important to use Grammar Structure in NLP? Communication is the act of sharing information through signals ... Read More
Support Vector Machines (SVMs) are supervised learning algorithms that can be used for both classification and regression tasks. SVMs are powerful algorithms that can be used to solve a variety of problems. They are particularly well−suited for problems where the data is linearly separable. However, SVMs can also be used to solve problems where the data is not linearly separable by using a kernel trick. In this article, we will explore the theory behind SVMs and demonstrate how to implement them for data classification in Python. We will provide a detailed explanation of the code, and its output, and discuss ... Read More
Alteryx is a user-friendly Data analytics platform. It is a robust data analytics and processing platform that enables users to extract, transform and process data from multiple sources and perform complex computation and analysis using a drag-and-drop interface. The reason behind the tool’s wide usage and fame is its no-code implementation of data preparation and analysis which streamlines business analysis in corporates. Getting Started with Alteryx Alteryx Designer is used for creating workflows for analyzing, blending data, and performing advanced analytics (such as predictive, spatial, and prescriptive) using the drag-and-drop user interface. A workflow in Alteryx consists of connected tools ... Read More
Neural Network is a widely used concept in the field of Artificial Intelligence and is based on the structure of the human brain. A neural network works in layers, the simplest one being a sequential model where the input of the current layer is the output of the previous layer. To create, train and test a neural network model, we can use a deep learning framework like Tensorflow in Python. Every neural network model is based on a few simple steps like taking data, making predictions, comparing predictions and finally, changing them to go closer to the target. ... Read More