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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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Mastering Keras: Best Practices for Optimizing Your Python Models
The popularity of Keras, a Python library for building and training deep learning models, has increased as deep learning evolves. It is known for its user-friendly API, which allows developers to quickly build, test, and deploy deep learning models. This article will cover the best practices for optimizing Keras models, including understanding Python Keras libraries,…
Read MoreEssential Keras Functions for Python Programmers
Python developers are likely to be familiar with constructing neural networks for deep learning applications. Although Python is a potent language that enables the development of complex applications, deep learning can be difficult. This is where Keras comes into play. Keras is a sophisticated neural network API that is coded in Python. It was created…
Read MoreTop Computer Vision Interview Questions and Answers
Computer vision is a rapidly growing field that combines computer science, mathematics and artificial intelligence to enable computers to interpret and understand images and videos. If you’re interviewing for a computer vision job, you may be asked a few questions designed to gauge your knowledge and expertise in the field. In this article, we discuss…
Read More5 Key Applications of Computer Vision Technology
Computer vision technology is a rapidly growing field with a wide range of real-world applications. From business to entertainment, from transportation to healthcare, computer vision technology is playing a crucial role in transforming various industries. In this article, we explore five key applications of computer vision technology and how they are revolutionizing entire industries. 1…
Read More5 Ways Computer Vision is Revolutionizing the Manufacturing Industry
The advent of computer vision technology has revolutionized several industries, and the manufacturing sector is no exception. From increasing revenue to reducing costs to improving worker safety, computer vision has transformed manufacturers around the world. In this article, we explore five ways computer vision is changing the manufacturing industry. Automatic Assembly Consumer expectations for quality…
Read MorePerforming Image Annotation using Python and OpenCV
Introduction Image annotation is a crucial task in the field of computer vision and machine learning. It involves labeling specific features in an image for training models to recognize those features in new images. Python and OpenCV provide a powerful combination of tools for performing image annotation efficiently and accurately. Understanding Image Annotation Image annotation…
Read MorePyTorch vs. TensorFlow: A Comprehensive Comparison
As the world of artificial intelligence (AI) continues to grow, so does the demand for deep learning frameworks. PyTorch and TensorFlow are two of the most popular deep learning frameworks available today. In this article, we will be providing you a comprehensive comparison between PyTorch and TensorFlow to help you make the right choice for…
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10 Tips for building Machine Learning Models with Scikit-learn
At the heart of machine learning is the ability to create models that can learn from data and make predictions based on new, never-before-seen data. Scikit-Learn is a powerful library for building machine learning models in Python. Here are our top 10 tips for building machine learning models with Scikit-Learn. 1 – Start with a…
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5 Tips to Maximize Performance when Working with Image Data in ML
When working with image data in machine learning, achieving optimal performance can be challenging. Fortunately, there are several best practices to follow to maximize model performance. Here are five tips to get you started: 1 – Get More Data One of the easiest ways to increase the accuracy of your image recognition model is to…
Read MoreHow to Build a Convolutional Neural Network for Computer Vision?
In today’s world, computer vision has become an integral part of many industries, including healthcare, retail and automotive. Convolutional neural networks (CNNs) are widely used for computer vision tasks such as image classification, object detection, and segmentation. In this article, we walk you through the process of creating a computer vision CNN with code examples.…
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10 Essential Tips for Building ML Models for Anomaly Detection
Anomaly detection is an important component of many data-driven applications. It enables us to efficiently identify anomalous behaviour and detect malicious activities that may otherwise be difficult to spot. In this blog post, we will discuss 10 essential tips for constructing machine learning models for anomaly detection with respect to data pre-processing, feature selection and…
Read MoreWhat is Text Mining and How it is Used in Data Science?
In the field of data science, text mining is a valuable technique used to extract valuable insights from unstructured data. This method involves extracting qualitative information from written text such as emails, social media posts and customer reviews. In this article, we will explore what text mining is, how it is used in data science,…
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