Your All-in-One Guide to Generative AI
What is Generative AI? Generative AI, or Generative Artificial Intelligence, is a type of artificial intelligence system and models that are designed to generate innovative, creative, or human-like content. These AI systems can generate new data or content rather than simply analyzing or processing existing data. Natural language processing, computer vision, music composition, art generation,…
Asmita Kar
An Introduction to Exponential Smoothing for Time Series Forecasting
Introduction to Exponential Smoothing: Exponential smoothing is a widely used time series forecasting technique that is particularly useful for forecasting data with a trend and/or seasonality. It is a simple yet effective method for smoothing out noisy data and making short to medium-term predictions. What Is Exponential Smoothing? Exponential smoothing is a time series forecasting…
Will Data Science ever rule the world?
With the ever-evolving business world, it is important that we know and learn how to adapt to the changing technologies. In this era of digitalisation, one who knows how to use data rules the world. With careful observation, you can see that data is everywhere. From social media platforms to multinational companies operating across the…
Types of Statistical Models in R for Data Scientists
Data Scientists are highly in demand across different industries for making use of the large volumes of data for analysisng and interpretation and enabling effective decision making. One of the most effective programming languages used by Data Scientists is R, that helps them to conduct data analysis and make future predictions. Statistical modeling in R…
Top Applications of Big Data across industries
What is Big Data? Gartner defines- “ Big Data are high volume, high velocity or high-variety information assets that require new forms of processing to enable enhanced decision-making, insight discovery and process optimisation.” Let’s go through an in-depth understanding of this definition followed by Big Data Applications in different industries. Big Data mainly refers to…
A Comprehensive Guide to Data Labelling
Machine Learning is becoming increasingly popular in the current tech-savvy era. the application of Machine Learning is everywhere from image recognition to complex forecast models. However, the most complex and expensive type of Machine Learning trend in use is Labelled Data. They require human expertise to tell a machine about the different data types to…
Top 10 Deep Learning Algorithms in Machine Learning
Introduction to Deep Learning Algorithms: Deep learning algorithms are a subset of machine learning techniques that are designed to automatically learn and represent data in multiple layers of abstraction. These algorithms have shown remarkable success in solving a wide range of complex tasks, such as image recognition, natural language processing, speech recognition, and more. At…
Principal Component Analysis in Machine Learning: A Comprehensive Guide
In the world of Data Science and Machine Learning which are growing exponentially, dimensionality reduction plays an important role. For the purpose of handling large and complex datasets, one of the most popularly used technique is the Principal Component Analysis. Whether you’re an experienced professional or just a beginner in Data Science, Principal Component Analysis…
Uncover the Secrets of Image Recognition using Machine Learning and MATLAB
Image Recognition using Machine Learning and MATLAB: With the advent of Machine Learning, it is now possible for computers to recognize and decipher objects, patterns, and other properties in digital photographs. In order to teach Machine Learning algorithms and teach the system different visual patterns, large datasets of labeled photos are used in this process. …
Algorithmic Bias and How to Avoid It – A Complete Guide
The following blog is a complete guide on Algorithmic Bias- What is it and How to Avoid it?, helping you learn about bias in Machine Learning. What is Algorithmic Bias? Algorithmic Bias refers to the presence of unfair or discriminatory outcomes produced by algorithms or machine learning models due to biased data or design choices….