Article Categories
- All Categories
-
Data Structure
-
Networking
-
RDBMS
-
Operating System
-
Java
-
MS Excel
-
iOS
-
HTML
-
CSS
-
Android
-
Python
-
C Programming
-
C++
-
C#
-
MongoDB
-
MySQL
-
Javascript
-
PHP
-
Economics & Finance
Machine Learning Articles
Page 42 of 56
What are Autoencoders in Deep Learning?
Introduction Data encodings are unsupervised learned using an artificial neural network called an autoencoder. An autoencoder learns a lower-dimensional form (encoding) for a higher-dimensional data to learn a higher-dimensional data in a lower-dimensional form, frequently for dimensionality reduction. Autoencoders Autoencoders are very useful in the field of unsupervised machine learning. They can be used to reduce the data's size and compress it. Principle Component Analysis (PCA), which finds the directions along which data can be extrapolated with the least amount of variance, and autoencoders, which reconstruct our original input from a compressed version of it, differ from one another. If ...
Read MoreWhat Are Self Organizing Maps - Kohonen Map?
Introduction Kohonen proposed the idea of a self-organizing map (SOM) in the first place. Since it is an unsupervised neural network that is trained using unsupervised learning methods to create a low-dimensional, discretized representation from the input space of the training samples, it is a way to minimise the dimensions of the data. A map is a common name for this representation. This article will walk through a Kohonen Map beginner's guide, which is a well-known self-organizing map. To begin, let's define what self-organizing maps are. Self-Organizing Maps Self-organizing maps, also known as Kohonen maps or SOMs, are ...
Read MoreHow Should a Machine Learning Beginner Get Started on Kaggle?
Kaggle is a social hub for data science and machine learning advocates where enthusiasts learn, explore, share, and collaborate to enhance their skills. Kaggle is like a playground for data, providing features like courses, competitions, discussions, and more. It provides users with a Jupyter notebook-like environment, saving time on setup and getting to work quickly. Kaggle is a great platform to practice and improve your skills. However, if you're new to Kaggle, the platform can be quite overwhelming to navigate. In this article, you’ll get a quick overview of how ML engineers can make the most of Kaggle. We'll guide ...
Read MoreNon-Negative Matrix Factorization
Introduction Non-Negative Matrix Factorization (NMF) is a supervised algorithm used to represent data into lower dimensions which reduces the number of features while preserving enough basic information to construct the original matrix from the reduced feature space. In this article, we will be going explore more about NMF and how it can be useful. Non-Negative Matrix Factorization NMF is used to reduce the dimensions of the input matrix or corpus. It uses factor analysis which gives less importance to less relevant words. The decomposition of the original matrix(which is a non-negative matrix) thus creates a product of two non-negative coefficients ...
Read MoreMultilingual Google Meet Summarizer and Python Project
Introduction Multilingual Google Meet summarizer is a tool/chrome extension that can create transcriptions for google meet conversations in multiple languages. During the COVID times people, they need a tool that can effectively summarize meetings, classroom lectures, and convection videos. Thus such a tool can be quite useful in this regard. In this article, let us have an overview of the project structure and explore some implementation aspects with the help of code. What this project is all about? This is a simple chrome extension that when enabled during a google meet session can generate meeting transcriptions and summarize the conversation ...
Read MoreImplementation of Teaching Learning Based Optimization
Introduction Teaching Learning Based Optimization (TLBO) is based on the relationship between a teacher and the learners in a class. In a particular class, a teacher imparts knowledge to the students through his/her hard work. The students or learners then interact with each other among themselves and improve their knowledge. Let us explore more about Teacher Learning Based Optimization through this article. What is TLBO? Let us consider a population p (particularly a class) and the number of learners l in the class. There may be decisive variables (subjects from which learners gain knowledge) for the optimization problem. Two modes ...
Read MoreImplementation of Particle Swarm Optimization
Introduction The Particle Swarm Optimization algorithm is inspired by nature and is based on the social behavior of birds in a flock or the behavior of fish and is a population-based algorithm for search. It is a simulation to discover the pattern in which birds fly and their formations and grouping during flying activity. Particle Swarm Optimization Algorithm In the PSO Algorithm, each individual is considered to be a particle in some high-dimensional search space. Inspired by the social and psychological behavior of people, which they tend to copy from other people's success, similar changes are made to the particles ...
Read MoreHow to Become an RPA Developer?
Introduction RPA stands for Robotic Process Automation. An RPA developer is a person who designs, maintains, builds, and implements RPA systems. In an organization, an RPA developer has the role to create optimized workflow processes and work cross-functionally with operations and business analysts. Scope of an RPA Developer Today the world is moving towards automation where organizations maximum repetitive processes to be automated as much as possible. Thus the demand for highly skilled RPA professionals has gained pace. With the right skill set, RPA developers can fill the in the respective domains. An RPA developer is essentially a software developer ...
Read MoreExploratory Data Analysis (EDA) - Types and Tools
Introduction Exploratory Data Analysis (EDA) is the process of summarization of a dataset by analyzing it. It is used to investigate a dataset and lay down its characteristics. EDA is a fundamental process in many Data Science or Analysis tasks. Different types of Exploratory Data Analysis There are broadly two categories of EDA Univariate Exploratory Data Analysis – In Univariate Data Analysis we use one variable or feature to determine the characteristics of the dataset. We derive the relationships and distribution of data concerning only one feature or variable. In this category, we have the liberty to use either ...
Read MoreDocument Retrieval using Boolean Model and Vector Space Model
Introduction Document Retrieval in Machine Learning is part of a larger aspect known as Information Retrieval, where a given query by the user, the system tries to find relevant documents to the search query as well as rank them in order of relevance or match. They are different ways of Document retrieval, two popular ones are − Boolean Model Vector Space Model Let us have a brief understanding of each of the above methods. Boolean Model It is a set-based retrieval model.The user query is in boolean form. Queries are joined using AND, OR, NOT, etc. A document ...
Read More