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    Fundamentals Of Ai For Beginners

    Posted By: ELK1nG
    Fundamentals Of Ai For Beginners

    Fundamentals Of Ai For Beginners
    Published 9/2024
    MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
    Language: English | Size: 1.11 GB | Duration: 0h 59m

    You are going to master the basics of AI and their models with Language models

    What you'll learn

    You are going to learn basics of AI

    You are going to learn various types of AI models

    You are going to learn language models

    You are going to learn how to use AI in various applications

    Requirements

    You need to have internet to take this course

    Description

    The development of AI relies heavily on machine learning a subset of AI that focuses on enabling machines to learn from data and improve their performance over time without being explicitly programmed. In machine learning, algorithms are trained using large datasets to recognize patterns, make decisions, and predict outcomes. A key technique is supervised learning, where algorithms are trained with labeled data, learning to map input to output. Other approaches include unsupervised learning, where the machine identifies patterns in unlabeled data, and reinforcement learning, where an agent learns by interacting with an environment and receiving feedback in the form of rewards or penalties.AI can be classified into two types: narrow AI and general AI. Narrow AI is designed for specific tasks, such as image recognition or language translation, and is the most common form seen today. General AI, still theoretical, would have the ability to perform any intellectual task that a human can, encompassing a broader range of capabilities.  It can struggle with tasks requiring common sense reasoning, emotional intelligence, or understanding context as deeply as humans do.AI is a rapidly evolving field that combines data, machine learning, and neural networks to replicate aspects of human intelligence, with immense potential for transforming industries and everyday life, yet requiring careful consideration of its societal implications.

    Overview

    Section 1: Introduction

    Lecture 1 Introduction

    Lecture 2 Transfer Learning

    Lecture 3 Language Modeling

    Lecture 4 Various types of models

    Lecture 5 Generative models

    Lecture 6 Language Modeling

    Lecture 7 Different Resources to learn

    Lecture 8 Architecture of Resources

    Lecture 9 Mapping in Languages

    If you want to learn with detailed examples for every concept, this course will be for you