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Achshah R M
Jul 26, 20245 min read
Agile Scrum Framework: Sprints, Artifacts and Events
Ever wondered how some of the world’s top companies like Google, Spotify, and Amazon manage to stay on top of their game? The secret lies...
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Achshah R M
Jul 23, 20244 min read
Kanban for Agile Project Management
Imagine you're running a busy kitchen in a popular restaurant. Orders come in fast, and you need to ensure that meals are prepared and...
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Achshah R M
Jul 22, 20245 min read
Why Agile is the Future of Software Development: Characteristics, Principles, and Values
In a world where technology evolves at lightning speed, sticking to rigid plans can be a recipe for disaster. Imagine being on a ship...
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Achshah R M
Jul 19, 20244 min read
Traditional Software Development Life Cycle Models: Waterfall, V-Shaped, and RUP
In today's fast-paced tech world, building software is like constructing a skyscraper. It requires a solid foundation, careful planning,...
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Achshah R M
Jul 19, 20243 min read
Avoiding Failure in Software Projects Using Project Management Models and Requirements Engineering
Ever wondered why some software projects soar to success while others crash and burn? Picture this: you’re on a thrilling adventure to...
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Achshah R M
Jul 19, 20244 min read
Exploring the Parallels Between Brain and Artificial Neural Networks
Have you ever wondered how our brains work? How does a tiny, seemingly insignificant cell called a neuron enable us to think, learn, and...
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Achshah R M
Jun 15, 20244 min read
Understanding Syntax and Semantics in NLP
Imagine a world where your computer understands not just the words you type or speak but also the meaning behind them. Thanks to Natural...
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Achshah R M
Jun 13, 20243 min read
The Rhythm of Speech: How Prosody Enhances NLP
Have you ever noticed how the same sentence can sound completely different depending on how it's said? This intriguing aspect of human...
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Achshah R M
May 27, 20242 min read
The NLP Revolution: From Early Skepticism to Cutting-Edge Technology
Natural Language Processing (NLP) represents the interaction between computers and humans through natural language. The key to improving...
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Achshah R M
May 23, 20244 min read
The Critical First Step in Data Analysis: The Ask Phase
The Ask phase is the first step in the data analysis process. In this phase, we typically define the problem we are trying to solve and...
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Achshah R M
May 17, 20243 min read
Introduction to Data Analysis: Analytical Skill, Data Life Cycle and Data Analysis Process.
"Data! Data! Data!... I can’t make bricks without clay!” – Sherlock Holmes Data is everywhere, and without data, we can’t solve any...
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Achshah R M
May 13, 20242 min read
OPTIMIZING DEEP Q-NETWORKS IN REINFORCEMENT LEARNING
Deep Q-Networks (DQN) have revolutionized the field of reinforcement learning by enabling agents to make optimal decisions in complex...
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Achshah R M
May 10, 20243 min read
INTRODUCTION TO DEEP Q-NETWORKS IN REINFORCEMENT LEARNING
Reinforcement Learning (RL) has come a long way with the advent of Deep Q-Networks (DQN), a sophisticated architecture that enables...
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Achshah R M
May 9, 20242 min read
ON-POLICY AND OFF-POLICY LEARNING: SARSA AND Q-LEARNING
In previous blogs, we explored various classifications in reinforcement learning (RL) such as model-free vs. model-based and DP vs. MC...
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Achshah R M
May 8, 20242 min read
EXPLORATION-EXPLOITATION DILEMMA IN REINFORCEMENT LEARNING
When agent performs actions suggested by the current policy it is said to be in exploitation mode. When agent tries actions it would have...
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Achshah R M
May 7, 20242 min read
TEMPORAL DIFFERENCE METHOD IN REINFORCEMENT LEARNING
Temporal Difference (TD) learning stands as a middle ground between Monte Carlo (MC) and Dynamic Programming (DP) methods, effectively...
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Achshah R M
May 6, 20242 min read
DYNAMIC PROGRAMMING VS MONTE CARLO METHOD IN REINFORCEMENT LEARNING
Dynamic Programming (DP) and Monte Carlo (MC) represent two foundational methods in reinforcement learning, each with distinct approaches...
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Achshah R M
May 3, 20242 min read
UNDERSTANDING VALUE ITERATION IN REINFORCEMENT LEARNING
In my previous post, we examined policy iteration, a two-step algorithm where the first step involves policy evaluation—calculating the...
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Achshah R M
May 1, 20243 min read
UNDERSTANDING POLICY ITERATION IN REINFORCEMENT LEARNING
Policy is the strategy used by a reinforcement agent to decide which action to make in the current state. A policy takes state as input...
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Achshah R M
Apr 30, 20242 min read
UNDERSTANDING ENVIRONMENTS IN REINFORCEMENT LEARNING
In the dynamic world of Reinforcement Learning (RL), the environment encompasses everything that the agent, or decision-maker, interacts...
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