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Trending Artificial Intelligence Blogs

21 Feb 2025 | 47 min read

18 Types of Regression in Machine Learning [Explained With Examples]

Regression in machine learning is a core technique used to model the relationship between a dependent variable (target) and one or more independent variables (features). Unlike classification (which predicts categories), regression deals with continuous numeric outcomes.

Pavan Vadapalli

21 Feb 2025 | 47 min read

18 Feb 2025 | 59 min read

Top 35 Linear Regression Projects in Machine Learning With Source Code

Linear regression is a supervised learning method in machine learning that uses a linear model to describe the connection between one or more predictor variables (features) and a continuous target variable. This technique tries to find an optimal line that minimizes the sum of squared errors, allowing you to produce better predictions.

Pavan Vadapalli

18 Feb 2025 | 59 min read

12 Feb 2025 | 26 min read

Top 40+ Exciting Deep Learning Project Ideas for Beginners [2025]

Deep learning is transforming industries, with the global market projected to reach $298.38 billion by 2032. Engaging in projects on deep learning is the most effective way to strengthen your skills and build a standout portfolio. Whether mastering neural networks, image recognition<

Kechit Goyal

12 Feb 2025 | 26 min read

12 Feb 2025 | 16 min read

Gini Index Formula: A Complete Guide for Decision Trees and Machine Learning

Want to make your machine learning models more accurate? The Gini Index is the secret. It’s a key metric in decision tree algorithms, helping you determine how pure or impure a split is. The lower the Gini Index, the more "pure" your split, which means your model can make more accurate predictions. When building decision tr

MK Gurucharan

12 Feb 2025 | 16 min read

11 Feb 2025 | 54 min read

Top 48 Machine Learning Projects [2025 Edition] with Source Code

Machine learning is a way to train computers with data so they can recognize patterns, predict outcomes, and learn from experience. You can see it in action when you get product recommendations or real-time language translations. Working on machine learning projects is one of the best ways to build your analytical skills, explore new too

Jaideep Khare

11 Feb 2025 | 54 min read

06 Feb 2025 | 20 min read

What is a Production System in AI? Types, Working, Examples, and More

Have you ever wondered how certain apps predict what you need and how machines figure out the next step without direct human input? Or you might have thought about designing AI solutions that reason like a human mind. If yes, a production system in AI holds your answers.

Pavan Vadapalli

06 Feb 2025 | 20 min read

06 Feb 2025 | 16 min read

Biological Neural Network and ANNs: Differences, Applications, and More

Imagine how the human brain handles a conversation or solves a puzzle. It’s powered by vast numbers of interconnected neurons that pass tiny signals to process information. This network of neurons is called the Biological Neural Network (BNN), and it adapts by changing the strength of connections as you learn new skills.

Pavan Vadapalli

06 Feb 2025 | 16 min read

06 Feb 2025 | 42 min read

Top 30 Raspberry Pi Projects for Students and Beginners in 2025

Raspberry Pi is a compact computer that brings coding and electronics to life. You can program it in Python, connect sensors for home automation or robotics, and even experiment with basic AI tasks. It’s simple enough if you’re starting, yet it can grow as you learn more advanced skills.

Kechit Goyal

06 Feb 2025 | 42 min read

Explore All Artificial Intelligence Blogs

What is DFS Algorithm? Depth First Search Algorithm Explained

The Depth-First Search algorithm is critical when working with data structures. Its recursive nature helps individuals examine and collect data by joining the vertices of a graph or a tree data structure. DFS in data structure have played a crucial role in searching for DFS trees and graph designs. The DFS algorithm has proven to be extremely important in studying data structures.

17 Feb 2025 | 9 min read

What is Deep Learning? How Does it Work, Career Opportunities, Salary

Artificial Intelligence and Machine Learning technologies are fueling and shaping next-generation computing

17 Feb 2025 | 8 min read

Bias vs Variance in Machine Learning: Difference Between Bias and Variance

A branch of artificial intelligence, machine learning allows machines to make predictions and analyse data. However, if the ML model is inaccurate, it can make prediction errors. These prediction errors are known as bias and variance. There is always a small difference between model and actual predictions. This is why these prediction errors – bias and variance – are constantly pre

17 Feb 2025 | 9 min read

What Is Ensemble Learning Algorithms in Machine Learning?

This guide will give you a thorough understanding of ensemble learning, ensemble methods in machine learning, ensemble algorithm, as well as important ensemble techniques, like boosting and bagging if you are a beginner who wants to understand in detail what an ensemble is or you want to brush up on your knowledge about variance and bias. This article’s goals are to present the idea of ens

17 Feb 2025 | 8 min read

What is Kruskal’s Algorithm? Steps, Examples, Overview

Introduction to Kruskal Algorithm Kruskal’s Algorithm is a popular algorithm used in graph theory to find the Minimum Spanning Tree (MST) of a weighted graph. The MST represents the subset of edges that form the most efficient way to connect all the vertices while minimizing the total weight. By employing Kruskal’s Algorithm, we can solve complex optimization problems

17 Feb 2025 | 9 min read

Top Advantages and Disadvantages of Machine Learning in 2024

Machine learning has been revolutionizing various industries, and as we enter 2025, it continues to be a driving force behind innovative advancements. Its ability to analyze vast data and make predictions without explicit programming has led to numerous benefits. However, with its increasing adoption, it’s crucial to understand the advantages and disadvantages of machine learning in real-world

17 Feb 2025 | 9 min read

What is Supervised Machine Learning? Algorithm, Example

Machine learning is everywhere – from government agencies, retail services, and financial institutions to the healthcare, entertainment, and transport sectors. It is intricately associated with our day-to-day lives, be it Netflix or Amazon giving online recommendations or your smartphone unlocking with face detection technology, machine learning and artificial intelligence have gained momentum

17 Feb 2025 | 9 min read

Understanding What is Feedforward Neural Network: Detailed Explanation

Feedforward neural networks are the essential fundamentals of artificial intelligence, used in speech recognition, medical imaging, and financial forecasting. Understanding what a feedforward neural network is essential to work with machine learning models that process structured data efficiently.

17 Feb 2025 | 15 min read

What is Virtual Reality Technology? Meaning, Devices & Examples

What is Virtual Reality? What is VR? VR is an immersive technology that provides users with a computer-generated world replicating realistic scenes and objects. A virtual reality headset or helmet creates a sensation of presence and engagement. VR allows users to engage with the virtual world and enjoy a higher immersion level by replicating a realistic environment.

17 Feb 2025 | 11 min read

AI Engineer Salary in India [For Beginners & Experienced] in 2025

Are you curious to learn about an AI engineer’s salary in India? As one of the most promising fields in the tech industry, AI offers exciting career opportunities across the country. The field offers lucrative job options for both fresh graduates and experienced professionals seeking a change. According to Sta

17 Feb 2025 | 17 min read

Curse of dimensionality in Machine Learning: How to Solve The Curse?

Machine learning can effectively analyze data with several dimensions. However, as the number of dimensions increases significantly, it becomes complex to develop relevant models. This phenomenon is known as the curse of dimensionality in machine learning, where high-dimensional spaces lead to abnormal results, making distance-based algorithms less effective and models prone to overfitting.

14 Feb 2025 | 8 min read

8 Pros of Decision Tree Regression in Machine Learning

Decision tree regression in machine learning is a model that predicts continuous values by learning decision rules from data features. While it is simple and interpretable, it has its own set of challenges. In this blog, we’ll explore the pros of decision tree

14 Feb 2025 | 16 min read

Top 29 Image Processing Projects in 2025 For All Levels + Source Code

Image segmentation divides an image into distinct parts with shared characteristics. You can apply different types of image segmentation methods, such as threshold-based methods, region-based approaches, or edge-based techniques, to isolate an area of interest and simplify your workflow. These methods help you detect objects and refine i

13 Feb 2025 | 38 min read

A Guide to the Types of AI Algorithms and Their Applications

Did you know the global AI market is set to grow by a whopping 28.45% by 2030? AI is transforming the way you work, live, and interact with technology. This rapid growth shows just how AI is impacting industries like healthcare, finance, and retail. AI algorithms are at the heart of this revolution, enabling machines

13 Feb 2025 | 19 min read

25 Must-Try Machine Learning Projects in Python for Beginners and Experts in 2025

Machine learning in Python has seen explosive growth, with a market share of 29.9%. It powers industries like healthcare, finance, and automotive with applications from predictive analytics to autonomous systems. This article explores 25 innovative Python machine learn

13 Feb 2025 | 28 min read

Understanding Gradient Descent in Logistic Regression: Guide for Beginners

Gradient descent in logistic regression updates the weights by reducing the log-loss; for example, if the initial weight is 0.5 and the gradient is -0.2, the new weight becomes 0.52 after an update. While the concept is simple, applying it correctly can be chal

13 Feb 2025 | 19 min read

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1.The above statistics depend on various factors and individual results may vary. Past performance is no guarantee of future results.

2.The student assumes full responsibility for all expenses associated with visas, travel, and related costs. upGrad does not provide any assurance or make representation...