Main Page
Welcome to Qbase
Your comprehensive knowledge base and collaborative platform
About QbaseQbase is a cutting-edge knowledge management platform designed to foster collaboration, innovation, and information sharing. Our platform serves as a central hub where knowledge meets community, enabling users to create, share, and discover valuable content across diverse domains. Whether you're a researcher, professional, student, or curious learner, Qbase provides the tools and environment to build comprehensive knowledge repositories that grow with your community's needs. Our MissionTo democratize knowledge sharing and create accessible, collaborative spaces where information transforms into wisdom, empowering communities to learn, grow, and innovate together. Featured Categories{{#widget:CategoryBox|category=Technology|color=#007bff|icon=💻}} {{#widget:CategoryBox|category=Science|color=#28a745|icon=🔬}} {{#widget:CategoryBox|category=Business|color=#ffc107|icon=💼}} {{#widget:CategoryBox|category=Education|color=#17a2b8|icon=📚}} {{#widget:CategoryBox|category=Health|color=#dc3545|icon=🏥}} {{#widget:CategoryBox|category=Arts|color=#6f42c1|icon=🎨}} |
Wiki Statistics85
Total Articles
123
Total Pages
267
Total Edits
1
Contributors
Quick ActionsCommunityJoin thousands of contributors who are building the future of knowledge sharing. Every contribution matters, from minor edits to major articles. |
Featured Articles
Introduction to Qbase
Learn the fundamentals of using Qbase effectively, from basic navigation to advanced features.
Best Practices Guide
Discover proven strategies for creating high-quality content and maintaining wiki standards.
Community Guidelines
Understanding our community standards and collaborative principles for a positive environment.
Technical Resources
Comprehensive technical documentation for developers and advanced users.
Recent Articles
12 June 2025
- 11:5011:50, 12 June 2025 Chemical Thermodynamics (hist | edit) [2,653 bytes] Thakshashila (talk | contribs) (Created page with "== Chemical Thermodynamics == '''Chemical Thermodynamics''' is the branch of thermodynamics that studies the interrelation of heat and work with chemical reactions or physical changes of state within chemical systems. It provides the framework to predict whether a reaction will occur spontaneously and to what extent it proceeds. === Basic Concepts === Chemical thermodynamics deals with the energy changes and equilibrium conditions in chemical reactions, focusing on va...")
- 11:4911:49, 12 June 2025 Entropy (hist | edit) [2,526 bytes] Thakshashila (talk | contribs) (Created page with "== Entropy == '''Entropy''' (symbol <math>S</math>) is a fundamental thermodynamic property that measures the degree of disorder or randomness in a system. It quantifies the number of microscopic configurations that correspond to a thermodynamic system's macroscopic state. === Definition === Entropy is related to the number of possible microstates (<math>\Omega</math>) by the Boltzmann equation: <math> S = k_B \ln \Omega </math> where: * <math>S</math> = entropy...")
- 11:4911:49, 12 June 2025 Phase Equilibrium (hist | edit) [2,990 bytes] Thakshashila (talk | contribs) (Created page with "== Phase Equilibrium == '''Phase equilibrium''' refers to the condition where multiple phases of a substance coexist in equilibrium without any net change in their amounts over time. It occurs when the chemical potential of each component is the same in all coexisting phases, ensuring no driving force for phase change. === Basics === In a system involving different phases (solid, liquid, gas), phase equilibrium is established when the rates of phase transitions (such a...")
- 11:4811:48, 12 June 2025 Thermodynamic Potential (hist | edit) [2,941 bytes] Thakshashila (talk | contribs) (Created page with "== Thermodynamic Potential == '''Thermodynamic potentials''' are scalar quantities used in thermodynamics to describe the equilibrium and spontaneous behavior of physical systems. They are functions of state variables such as temperature, pressure, volume, and entropy, and provide criteria for spontaneous processes and equilibrium under different constraints. === Overview === Thermodynamic potentials combine the system's internal energy with other thermodynamic paramet...")
- 11:4711:47, 12 June 2025 Gibbs Free Energy (hist | edit) [2,466 bytes] Thakshashila (talk | contribs) (Created page with "== Gibbs Free Energy == '''Gibbs Free Energy''' (denoted as <math>G</math>) is a thermodynamic potential that measures the maximum reversible work a thermodynamic system can perform at constant temperature and pressure. It is an important concept in chemistry and physics, used to predict the spontaneity of chemical reactions and phase changes. === Definition === Gibbs Free Energy is defined as: <math>G = H - TS</math> where: * <math>G</math> = Gibbs free energy *...")
11 June 2025
- 11:4411:44, 11 June 2025 Convolutional Neural Network (hist | edit) [3,251 bytes] Thakshashila (talk | contribs) (Created page with "== Convolutional Neural Networks (CNNs) == A '''Convolutional Neural Network (CNN)''' is a type of deep learning model specially designed for working with '''image data''' 📷. CNNs are widely used in computer vision tasks like image classification, object detection, and face recognition. === 🧠 Why CNNs for Images? === Images are large (millions of pixels), and fully connected neural networks don't scale well with size. CNNs solve this by using convolution operati...")
- 11:1211:12, 11 June 2025 Backpropagation (hist | edit) [3,012 bytes] Thakshashila (talk | contribs) (Created page with "== Backpropagation == '''Backpropagation''' (short for "backward propagation of errors") is a fundamental algorithm used to train neural networks. It calculates how much each weight in the network contributed to the total error and updates them to reduce this error. === 🧠 Purpose === The main goal of backpropagation is to: * Minimize the '''loss function''' (error) 📉 * Improve model accuracy over time by adjusting weights 🔧 === 🔁 How It Works (Step-by-Ste...")
- 10:0910:09, 11 June 2025 Exploding Gradient Problem (hist | edit) [2,974 bytes] Thakshashila (talk | contribs) (Created page with "== Exploding Gradient Problem == The '''Exploding Gradient Problem''' is a common issue in training deep neural networks where the gradients grow too large during backpropagation. This leads to very large weight updates, making the model unstable or completely unusable. === 📈 What Are Gradients? === Gradients are computed during the backpropagation step of training. They help the model understand how to change its weights to reduce error. :<math> \text{Gradient} =...")
Powered by MediaWiki • Built with ❤️ by the Qbase Community