Articles for author: Mohit Uniyal

Mohit Uniyal

EM Algorithm in Machine Learning

EM Algorithm In Machine Learning

In machine learning, statistical models often rely on hidden information or latent variables—elements of data that are not directly observed but influence the overall outcomes. Identifying the optimal parameters for these models becomes challenging when such latent variables are present. The Expectation-Maximization (EM) algorithm offers a powerful solution to this problem. It is designed to ...

Mohit Uniyal

What is Quantum Machine Learning

What is Quantum Machine Learning?

Quantum Machine Learning (QML) is an exciting and emerging field that combines quantum computing and machine learning. While classical machine learning has made great strides, it faces limitations, especially when solving highly complex problems that require enormous computational power. This is where QML comes into play—it uses the principles of quantum mechanics to potentially solve ...

How To Learn Artificial Intelligence (AI)

How To Learn Artificial Intelligence (AI) From Scratch

Artificial Intelligence (AI) has rapidly become one of the most transformative technologies of the 21st century. From virtual assistants like Siri and Alexa to recommendation systems on Netflix and Amazon, AI is everywhere. Its applications span across industries such as healthcare, finance, transportation, and retail, making it an essential skill for future professionals. Whether you’re ...

Mohit Uniyal

types of data analytics

Types of Data Analytics: 4 Important Types

Data has become one of the most valuable resources in today’s world, powering everything from business decisions to product recommendations. With every passing second, more data is being generated across various platforms and industries, making it essential to analyze and interpret this information effectively. Data analytics plays a crucial role in helping organizations process large ...

Mohit Uniyal

Convolutional Neural Network In Machine Learning

Convolutional Neural Network (CNN) in Machine Learning

Convolutional Neural Networks (CNNs) are a type of deep learning model commonly used in image recognition tasks. Unlike traditional neural networks, CNNs are designed to automatically detect patterns from images, making them highly efficient in visual data processing. Deep learning, a subset of machine learning, enables machines to mimic the way humans learn from experience, ...

Mohit Uniyal

collaborative filtering

What is Collaborative Filtering?

Collaborative filtering is a core technique used in recommendation systems. It plays a crucial role in personalizing experiences for users on platforms such as e-commerce sites, streaming services, and social media networks, improving engagement by suggesting relevant items based on user behavior patterns. What is Collaborative Filtering? Collaborative filtering is a method used to predict ...

Mohit Uniyal

one hot encoding

One Hot Encoding In Machine Learning

In machine learning, models primarily work with numerical data. However, many real-world datasets include categorical variables, such as colors, locations, or types of products. To build effective machine learning models, it’s essential to preprocess these categorical features and transform them into a format that algorithms can interpret. One-hot encoding is a popular method for converting ...

Mohit Uniyal

feature extraction in machine learning

Feature Extraction in Machine Learning

In machine learning, raw data in its initial form often contains noise, irrelevant information, or excessive dimensionality, making it challenging to use directly in models. This is where feature extraction plays a crucial role. It involves transforming raw data into a more informative and usable format, which enhances model performance and reduces computational costs. For ...

Mohit Uniyal

hierarchical clustering in machine learning

Hierarchical Clustering in Machine Learning

Hierarchical clustering is a powerful unsupervised machine learning algorithm used to group data points into a hierarchy of clusters. It is particularly useful when the number of clusters is not predefined, and it helps to visualize the data’s structure through a dendrogram, which represents the nested clustering relationships. Hierarchical clustering finds applications across various domains, ...

Mohit Uniyal

Bias and Variance in Machine Learning

Bias and Variance in Machine Learning

Machine learning models aim to make accurate predictions by learning from data. However, two critical factors—bias and variance—affect the performance of these models. Understanding and balancing these factors is essential for building models that generalize well to new data. Bias refers to errors due to overly simplistic assumptions in the learning algorithm, while variance measures ...