Artificial Intelligence
Code Generation with Generative AI Writing code has traditionally required years of practice and understanding of programming languages. But with the rise of generative AI, coding is becoming more accessible to everyone — from beginners to seasoned developers. In this tutorial, we’ll explore how AI-powered tools can assist in generating, understanding, and debugging code. Whether […]
AI Hallucination AI Hallucination refer to instances where an AI model, LLM, malfunction or misbehave, generating inaccurate or false information. The problem is that these models present inaccurate information to you as accurate. AI hallucinations occur when an AI outputs false or made-up information. They are common in large language models (LLMs) due to data […]
Introduction to Perplexity.ai Tool Perplexity.ai is an advanced AI tool designed to help users access answers to their questions in an efficient and user-friendly way. It works by using powerful language models to provide quick, accurate, and context-aware responses to text-based queries. With its easy-to-use interface, Perplexity.ai helps users find relevant information from a variety […]
AI Engineer Roles Artificial Intelligence (AI) Engineers are professionals who design, develop, and implement AI models and systems. They work with data, machine learning algorithms, and various AI frameworks to create intelligent applications that solve real-world problems. AI engineers bridge the gap between data science and software development, ensuring AI-driven solutions are efficient, scalable, and […]
Types of Machine Learning Machine Learning encompasses algorithms and methodologies designed to enable computers to learn from data and make predictions or decisions without being explicitly programmed. The main types of machine learning are as follows: Supervised Learning Unsupervised Learning Reinforcement learning Deep Learning Supervised Learning Supervised learning algorithms learn from labeled data, predicting […]
The machine learning life cycle is the end-to-end process of developing, deploying, and maintaining the ML model. ( Machine Learning model)