macine-learning

Machine Learning By Krista Williams

What is Machine Learning? Machine learning (ML) is the study of computer algorithms that can improve automatically through experience and by the use of data. It is part of Artificial Intelligence

Examples of Machine Learning Image-recognition - Image recognition is the creation of a neural network that processes all the pixels that make up an image. Speech identification - Machine learning can convert speech into text.

Types of Machine Learning? 1. Supervised learning 2. Semi supervised learning 3. Unsupervised learning 4. Reinforcement learning

Supervised learning Supervised learning is an approach to creating artificial intelligence (AI), where a computer algorithm is trained on input data that has been labeled for a particular output. Semi-supervised learning is an approach to machine learning that combines a small amount of labeled data with a large amount of unlabeled data during training.

Unsupervised learning Unsupervised learning is a type of algorithm that learns patterns from untagged data. The hope is that through mimicry, which is an important mode of learning in people, the machine is forced to build a compact internal representation of its world and then generate imaginative content from it. Reinforcement learning Reinforcement Learning(RL) is a type of machine learning technique that enables an agent to learn in an interactive environment by trial and error using feedback from its own actions and experiences.

Goal of Machine learning Its goal and usage is to build new and/or leverage existing algorithms to learn from data, in order to build generalizable models that give accurate predictions, or to find patterns, particularly with new and unseen similar data. For any kind of college academic assignment help Connect College Homework Help

Future of Machine learning With present development in the machine learning, we can imaginerobots manufacturing more in coming future. with many advantages, we can reduce cost in manufacturing using machine learning, can enhance quality control and improve supply chain management

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Presentation Transcript

Learning and Lifelong learning

Learning About Learning

Reinforcement Learning : Learning Algorithms

Learning E-Learning: Introduction

How often our school’s coffee macine works ?

Learning and Learning LiveCode

Learning styles Learning Preferences Learning Strategies

HUMAN LEARNING AND LEARNING

Deep Learning Feature Learning Representation Learning Generative Learning

Learning about learning

Machine learning: Unsupervised learning

Learning about learning

Mobility + Learning = Mobile Learning

Active Learning = Deep Learning

Learning and Learning Disabilities

E- leaRning b- leARning m- leARning

Learning Unit – learning consultant

Learning inside, learning outside

Learning Teaching Teaching Learning

Learning Technologies E-Learning