Featured Articles
Rajesh Yerremshetty Zero to Python Hero – Part 5/10: Essential Data Structures in Python: Lists, Tuples, Sets & Dictionaries
The fundamental way of storing, accessing and manipulating of data in python is data structures. Python provides an convenient and adaptable collection of objects to store and data and sort it in different ways, be it a list, a tuple,...
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Naveen Pandey Top 5 Skills Every Engineer Should Learn in 2026
The world of engineering is changing faster than ever before. Technologies that were once futuristic like artificial intelligence, machine learning, and cloud computing are now driving industries forward. By 2026, the engineers who thrive won’t just be the one who...
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Zero to Python Hero - Part 4/10 : Control Flow: If, Loops & More (with code examples)
A major element of any programming language is the capability to take decisions and repeat them -this is the so-called control flow. Control flow is a feature available in Python that enables us to have the control of how code...
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Zero to Python Hero - Part 3/10 : Understanding Type Casting, Operators, User Input and String formatting (with Code Examples)
Type Casting & Checking What is Type Casting? Type casting (also called type conversion) is the process of converting a value from one data type to another. It’s like translating between different languages – sometimes you need to convert a number to...
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Dynamic Programming in Reinforcement Learning: Policy and Value Iteration
The core topic of reinforcement learning (RL) Dynamic Programming in RL: Policy and Value Iteration Explained provides fundamental solutions to resolve Markov Decision Processes (MDPs). This piece teaches about Policy Iteration and Value Iteration alongside their mechanisms as well as...
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Top 10 AI and ML Project Ideas for 2023
Artificial Intelligence (AI) is a rapidly growing field that can seem daunting to beginners. However, there are many basic AI projects that beginners can take up to gain experience and knowledge. In this blog post, we will explore 10 AI and ML projects ideasthat are perfect for beginners. These projects cover a wide range of…
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ResNet(Residual Networks) Explained – Deep Learning
In this blog post, we will explore the concept of residual networks in deep learning. Residual networks, also known as ResNets, have revolutionized the field of deep learning by enabling the training of extremely deep neural networks. We will discuss the motivation behind ResNets, their architecture, and how they address the challenges of training deep…
Read MoreSigmoid Activation Function in Detail Explained
When it comes to artificial neural networks, the Sigmoid activation function is a real superstar! It might sound like a fancy term, but don’t worry; we’re going to break it down in a way that even your grandma would understand. What’s the Buzz About Activation Functions? Before we zoom in on the Sigmoid activation function,…
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Efficient Data Manipulation with Apply() Function in Pandas
If you’re a data enthusiast like me, you’ve probably dabbled in the world of Python and Pandas, the go-to library for data manipulation and analysis. Now, imagine you have a massive dataset with thousands of rows, and you want to perform some custom operations on it. Well, don’t fret! Pandas has your back, and it…
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Implementing Linear Regression from Scratch with Python
Linear regression is a fundamental machine learning algorithm that allows us to predict numerical values based on input data. In this article, we will see how to implement linear regression from scratch using Python. We will break down the code into simple steps, explaining each one along the way. So, let’s understand how linear regression…
Read MoreUnderstanding the Softmax Activation Function: A Detailed Explanation
The Softmax activation function is one of the most important activation function in artificial neural networks. Its primary purpose is to transform a vector of real numbers into a probability distribution, enabling us to make informed decisions based on the output probabilities. In this article, we will figure out the workings of the Softmax activation…
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Enhancing Image Visibility with Adaptive Thresholding
In this article we will be working on Enhancing Image Visibility with Adaptive Thresholding. You must have come across images that appear too dark or lack the necessary contrast to make out important details? Whether it’s a poorly lit photograph or a scanned document, such images can be challenging to interpret. Fortunately, there’s a powerful…
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Parkinson’s Disease Detection using Machine Learning Algorithm
In this step-by-step tutorial we will walk through the step-by-step process of building Parkinson’s Disease detection using machine learning. Parkinson’s Disease is a neurodegenerative disorder that affects millions of people worldwide. Early detection of the disease is crucial for effective management and treatment. In this article, we will explore how machine-learning techniques can be employed…
Read MoreDay 5: Everything you need to know about Activation Functions in Deep learning
Deep learning is a powerful area of artificial intelligence that has received a lot of attention in recent years. One of the main components of deep learning models is the activation function. Activation functions play a crucial role in determining the output of a neural network. In this article, we will dive deep into understanding…
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How to get internship into Data Science
In today’s IT industry, data science has become a prominent buzzword. With many job opportunities and lucrative salaries, this is an exciting field to explore. If you want to start your career in data science, securing an internship is a great starting point. In this article, I’ll cover some valuable tips and tricks to help…
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Precision, Recall & F1: Understanding the Differences Easily Explained for ML
When it comes to evaluating the performance of our machine learning models, two main metrics are considered: precision and recall. These metrics are the basis for evaluating the effectiveness and reliability of the model’s prediction. In this article, we will discuss the complexities of precision and recall, their significance, and how they are used in…
Read MoreThe Differences between Sigmoid and Softmax Activation function?
In the field of neural networks, activation functions play an important role in transforming linear output into nonlinear, allowing models to learn complex patterns efficiently. Two commonly used activation functions are the Sigmoid and Softmax functions. In this article, we will be looking at the differences between these two activation functions and their respective use…
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