Author: Naveen
Naveen PandeyHow 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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10 Common Data Science Interview Questions and How to Answer Them?
Data science has become a very competitive field and it is important to prepare for data science interviews if you are looking for your dream job. As part of the interview process, you can expect to be asked a number of questions to assess your knowledge, skills and experience in the field. In this blog…
Read MoreTop 5 Natural Language Processing Libraries for Data Scientist
In this blog post we are going to talk about Natural Language Processing (NLP) which is one of the branches of machine learning which focuses on teaching machines to understand human language. it has multiple applications, from chatbots to sentiment analysis, and is an important skill in the data scientist’s toolbox. let’s look at five…
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10 Essential Python Libraries for Data Science in 2023
Data Science is a constantly evolving field, and with freshly technologies emerging, it’s important to keep up with the latest tools and libraries. In this article, we’ll discuss 10 essential Python libraries that all data scientist should know in 2023. These libraries will serve you to analyze, visualize, and model data more efficiently, and ultimately…
Read More10 Tips for Building Machine Learning Models for TensorFlow
Building a machine learning model using TensorFlow can be a daunting task, but it doesn’t have to be. Here are ten tips for building a successful machine learning model with TensorFlow. 1 – Preprocess Your Data: Preprocessing is essential in machine learning. Before feeding the data to a model, it is necessary to preprocess it…
Read More10 Tips for Building Machine Learning Models with PyTorch
Machine learning is a rapidly growing field, and PyTorch is one of the most popular frameworks for building machine learning models. It is an open-source machine learning library based on the Torch library written in Python. With its easy-to-use interface and excellent GPU acceleration support, PyTorch has become the choice of many researchers and developers.…
Read MoreHow to use Generative Adversarial Networks in Machine Learning?
Generative Adversarial Networks (GANs) are a type of simple machine learning algorithmic rule that has gained significant attention in recent years. GANs can generate recently data that resembles the original dataset, which makes them ideal for tasks so much as image and speech generation. If you’re interested in learning how to use GANs in your…
Read More5 Tricks for Working with Large Datasets in Machine Learning
In this article we will be looking at 5 Tricks which can help you workings with large number of data in machine learning. Machine learnedness can help businesses and organizations to make more informed decisions. However, dealing with large amount of data is the one of the biggest challenges you come across while workings in…
Read MoreHow to Handle Skewed Data in Machine Learning
Introduction: Data is the fuel that drives the success of machine learning algorithms. But not all data is created equal. One problem that can arise when working with datasets is skewed data. Skewed data occurs when the distribution of a variable is not evenly distributed, resulting in an unbalanced data set. This can negatively affect…
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10 Advanced NumPy Functions You Need to Know
Numpy is a powerful Python library for scientific computing and data analysis. It provides a wide range of functions and tools for manipulating multidimensional arrays and matrices. In this blog post, we’ll talk discuss 10 advanced Numpy features you should know to get the most out of this library. 1 – np.linspace() The np.linspace() function…
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Zero to Python Hero – Part 5/10: Essential Data Structures in Python: Lists, Tuples, Sets & Dictionaries
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Top 5 Skills Every Engineer Should Learn in 2026
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Zero to Python Hero - Part 4/10 : Control Flow: If, Loops & More (with code examples)
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Zero to Python Hero - Part 3/10 : Understanding Type Casting, Operators, User Input and String formatting (with Code Examples)
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Dynamic Programming in Reinforcement Learning: Policy and Value Iteration
Latest Articles
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Zero to Python Hero – Part 6/10: Functions and Modules in Python
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Zero to Python Hero – Part 5/10: Essential Data Structures in Python: Lists, Tuples, Sets & Dictionaries
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Top 5 Skills Every Engineer Should Learn in 2026
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Zero to Python Hero - Part 4/10 : Control Flow: If, Loops & More (with code examples)
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Zero to Python Hero - Part 3/10 : Understanding Type Casting, Operators, User Input and String formatting (with Code Examples)
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Zero to Python Hero - Part 2/10 : Understanding Python Variables, Data Types (with Code Examples)
