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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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3 Important Neural Network Architectures Explained
1. Perceptron The perceptron is the most basic of all neural networks, being a fundamental building block of more complex neural network. If simple connects an input cell and an output cell. 2. Feed-Forward Network The feed-forward network is a collection of perceptions’. In which there are three fundamental types of layers – input layers,…
Read More3 Concepts Every Data Scientist Must Know Part – 2
1. Bagging and Boosting Bagging and Boosting are two different ways used in combining base estimators for ensemble learning (Like random forest combining decision trees). Bagging means aggregating the predictions of several weak learners. We can think of it combining weak learners is used in parallel. The average of the predictions of several weak learners…
Read MoreWhat is the Normal Distribution?
Probability distribution is the function that shows the probabilities of the outcome of an event or experiment. Consider a feature (i.e., column) in a dataframe. This feature is a variable and its probability distribution function shows the likelihood of the values it can take. Probability distribution function are quite useful in predictive analytics or machine…
Read MoreImportant Deep learning Concept Explained Part – 2
Converge Algorithm that converges will eventually reach an optimal answer, even if very slowly. An algorithm that doesn’t converge may never reach an optimal answer. Learning Rate Rate at which optimizers change weights and biases. High learning rate generally trains faster but risks not converging whereas a lower rate trains slower. Numerical instability Issues with…
Read MoreImportant Deep learning Concept Explained Part – 1
Neuron Node is a NN, typically taking in multiple input values and generating one output value by applying an activation function (nonlinear transformation) to weighted sum of input values. Weights Edges is a NN, the goal of training is to determine the optimal weight for each feature; if weight = 0, corresponding feature does not…
Read MoreRussia-Ukraine War Data Analysis Project using Python
In this article I will take you through the task of Analyzing the Russia-Ukraine war Dataset using Python. The dataset that I am using for the task of analysis the Ukraine and Russia War is downloaded from Kaggle. You can download russia-ukraine equipment dataset from here and russia-ukraine personnel losses dataset from here. Now let’s import…
Read More3 Concepts Every Data Scientist Must Know Part – 1
Central Limit Theorem We first need to introduce the normal (gaussian) distribution for central limit theorem to make sense. Normal distribution is a probability distribution that look like a bell. X-axis represents the values and y-axis represents the probability of observing these values. The sigma values represent standard deviation normal distribution is used to represent…
Read MoreMost Common Feature Scaling methods in Machine Learning
Definition Feature scaling is the process of normalizing the range of feature in a dataset. Real-world datasets often contain features that are varying in degrees of magnitude, range and units. Therefore, in order for machine learning models to interpret these features on the same scale, we need to perform scaling. Feature scaling makes the model…
Read MoreTop 8 Deep Learning Algorithms
Convolutional Neural Networks CNN’s popularly known as ConvNets majority consists of several layers and are specifically used for image processing and detection of objects. It was developed in 1998 by Yann LeCun. CNNs have wide usage in identifying the image of the satellites, medical image processing, series forecasting, and anomaly detection. CNNs process the data…
Read MorePython Interview Questions – Part 1
1. What is the difference between indexing and slicing? Indexing is the extracting or lookup one or particular values in a data structure, whereas slicing retrieves a sequence of elements. 2. What is the lambda function? Example: X = lambda I, j: I + j Print (x(4, 6)) Output: 10 3. Explain zip() and enumerate()…
Read MoreWhat are Pickling and Unpickling?
Pickling Pickling and unpickling are terms commonly used in the context of Python programming and refer to the process of serializing and deserializing objects. In simple terms, pickling is the process of converting a Python object into a byte stream, while unpickling is the process of converting the byte stream back into a Python object.…
Read MoreWhat Advantage does the NumPy Array have over a nested list?
NumPy arrays offer several advantages over nested lists in Python. Let’s see some of the key advantages: Overall, the advantages of NumPy arrays over nested lists make them an excellent choice for numerical computations, large datasets, and scientific computing tasks, providing performance improvements and ease of use. Popular Posts
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