Aditya Chatterjee's Blog, page 2

Basics of OOP in Java: Contact Book Program

Table of ContentsPrerequisitesIntroductionThe Contact classThe ContactBook classPutting it all together - The ContactBookClient classSummaryKey ConceptsConclusionPrerequistes

This OpenGenus article is intended for those who have knowledge of basic Java syntax such taking input/output from the user using Scanner, data types and variables, loops and conditions, classes and objects, exception handling and ArrayList and are ready to build their first project using object-oriented programm...

Exploring Randomness and Statistical Simulations in Online Games

The ever-changing online gaming world is built with randomness as an integral part. Randomness is needed because it gives variety and fun purely from the unpredictability of the fate of the characters' abilities.

However, the relentlessness of such simulations is built around a technical, rigorous framework beneath the randomness players put up with. These are fair and unpredictable; all players are on a level field.

Randomness in Game Design

Pixabay

A big part of gaming is randomness, not just...

Dodgeball game in PyGame [with source code]

Game development is an exciting and interesting area to explore for people who have just finished learning web/app development, or any person who's enthusiastic about gaming and coding. To get started with game development, you must know at least one programming language such as C++, C#, Java or Python. Generally, to develop a 2D/3D game, it would be more convenient to learn a game engine so that much of the complexity of designing your game graphics, rendering audio, animation, etc. is abstract...

Active Learning: How Machines Learn Better with Human Guidance

In machine learning, a large amount of labeled data is needed to train accrurate models. However labelling data can be time consuming and expensive, especially in domains like healthcare or autonomous driving. Active learning solves this problem by letting the model query a human expert for labels on the most uncertain or informative data points. This reduces the amount of labeled data needed which then speeds up the training process.

WHAT IS ACTIVE LEARNING?

Active learning is a type of machine...

Retrieval Augmented Generation (Concepts)

Generative AI (GenAI) is highly effective at producing text responses using Large Language Model (LLM), which are trained on vast amounts of data. The advantage is that the generated text is usually easy to understand and provides detailed, widely applicable answers to the input, or generally known as "prompts". However, the drawback is that AI's responses are limited to the data it was trained on, which may be outdated. In a company-specific AI chatbot, this can result in answers that don't ref...

Bilinear Upsampling

In this OpenGenus article, let us discuss Bilinear Upsampling which pops up quite bit in regards to image manipulation and processing in a greater detail.

ContentsIntroduction : UpsamplingUpsampling TechniquesBilinear UpsamplingPseudocode ImplementationPrecautionsApplicationsKey-takeawaysIntroduction : Upsampling

In image processing, upsampling refers to the process of increasing the resolution or dimensions of an image by adding new pixels between the existing ones. The goal is to mak...

Chameleon Hash: Balancing Security and Flexibility in Cryptographic Hashing

Key Takeaways

Chameleon hashes allow authorized users to create hash collisions using a secret trapdoor key, which enables them to alter data while still producing valid hashes.They reduce the need for recomputing hashes for entire datasets.Chameleon hashes are useful in secure digital signatures, mutable blockchains, and privacy-preserving systems.Potential vulnerabilities, such as trapdoor disclosure, must be managed to ensure system integrity.Continued advancements aim to enhance the sec...

Physical and Architectural Constraints in CPUs and GPUs

Key Takeaways:

Quantum and Thermal Limits: As transistors shrink, quantum effects and thermal constraints pose challenges to CPU and GPU efficiency.Transistor Scaling Issues: Transistors under 5 nm face increased leakage and unpredictable behavior, which limits reliability.Thermal Management: Increasing power and heat generation requires advanced cooling systems as traditional methods are no longer sufficient.Heat Dissipation Limits: Materials like copper and carbon nanotubes have limits, an...

slice_scatter op in PyTorch

Table of contentsIntroductionUsage
i. Key Features
ii. Basic Usage
iii. Advanced Applications
iv. CautionAlternativesConclusionIntroduction

torch.slice_scatter is a tensor manipulation function in PyTorch that allows us to embed values from one tensor into another at specified locations. This operation generates a new tensor with fresh storage rather than modifying the original tensor. This capability is particularly useful for various data processing tasks in both deep learning and machi...

Designing ResNet50 in PyTorch

Table of contentsIntroductionUnderstanding ResNet
i. Key contributions
ii. ResNet verisonsKey componentsPrerequisitesImplementationConclusionIntroduction

As the number of layers increase in a CNN architecture, the more chances of exploding gradient problem and degradation in performance. In order to avoid this, the residual network was introduced in a research paper published by the Microsoft Research team.

The dataset used in this implementation is the Apple Leaf Disease Dataset from K...