1 / 9

Exploring Machine Learning

Machine learning is becoming more and more crucial for businesses to understand client behavior, run their operations, and create new products. For many businesses, it now serves as a competitive differentiation. Machine learning development company helps drive operational growth and efficiency with advanced Artificial Intelligence (AI) and Machine Learning (ML) consulting services. Want to become a prominent leader in the business industry with machine learning? Hexaview drives Machine learning development services and potency for your business.

hexaview
Download Presentation

Exploring Machine Learning

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Exploring Machine Learning and its Three Pillars

  2. What Is Machine Learning? Machine Learning is a branch of Artificial Intelligence (AI), and as the name implies, it is an artificial human brain that attempts to imitate how a human responds to a particular situation, regardless of whether he has previously encountered that situation or not. Because no system is perfect, Machine Learning, also known as 'Artificial Intelligence,' can help with decision-making errors. As a result, there is always room for advancement in the field of Machine Learning. ARTIFICIAL INTELLIGENCE MACHINE LEARNING DEEP LEARNING 2 www.hexaviewtech.com

  3. Three Pillars of Machine Learning SUPERVISED MACHINE LEARNING • REINFORCEMENT • LEARNING UNSUPERVISED 3 www.hexaviewtech.com

  4. Supervised Learning Supervised Machine Learning is a learning algorithm that uses labelled training data to predict outcomes for unlabeled data. Supervised learning involves training the machine with well-labeled data. It means that some data has already been tagged with the correct answers. Learning in the presence of a supervisor or teacher can be compared to this. It takes time and technical expertise from a team of highly skilled data scientists to successfully build, scale, and deploy accurate supervised machine learning models. Labeled Data Model Training Prediction Triangle Circle Labels Rectangle Circle Test Data Hexagon Triangle 4 www.hexaviewtech.com

  5. There are two types of Supervised Learning Regression: Continuous data problems include house prices, ages, weight, and so on. Consider the temperature prediction case. In this case, regardless of whether the weather tomorrow will be hot or cold, our classifier will attempt to predict the numerical temperature of tomorrow based on previous learnings. Regression What is the temperature going to be tomorrow? Classification problem trains the algorithm to classify the test data into one of several classes or groups. Assume we have trained our model to predict whether the temperature will be hot or cold tomorrow based on past patterns or learnings, which is classified as Classification Supervised Learning. Classification Will it be Cold or Hot tomorrow? 5 www.hexaviewtech.com

  6. Unsupervised Learning Now that we know that supervised learning uses labelled data to train our classifier. The primary distinction between supervised and unsupervised learning is the absence of cleaned labelled data in unsupervised learning. Unsupervised learning is a self-learning algorithm that seeks patterns or useful information in unlabeled data. A model receives data without guidance in unsupervised learning.In Unsupervised learning, a model receives the dataset without labels. It is impossible to find the relationship between data by hand, especially when the data is large. In that case, pattern-based grouping is used, and the model uses comparisons to predict the output. 6 www.hexaviewtech.com

  7. Reinforcement Learning People frequently become perplexed when it comes to reinforcement learning Reinforcement learning teaches algorithms to react to their surroundings on their own. An agent, in particular, has a starting and ending point (AI-driven system). Using hit and trial, the algorithm learns to reach an endpoint. Self-driving cars and automatic vacuum cleaners are popular examples of reinforcement learning. When an agent takes the correct step, he or she is rewarded; otherwise, the incorrect step is punished. 7 www.hexaviewtech.com

  8. In Nutshell Supervised learning is defined as learning with supervision (labeled data). Unsupervised learning is learning without guidance. Reinforcement learning is a type of learning in which a machine or agent interacts with its surroundings and performs actions based on hit and trial. 8 www.hexaviewtech.com

  9. About Us Together we foster creativity, innovation & an empowered workplace Official Blog Link https://hexaviewtech.com/blog/exploring-machine-learning-and-its-three-pillars Transforming businesses using advanced technology by providing excellence in project, process, & product delivery and significantly impacting businesses & society around the world. Contact Us www.hexaviewtech.com +1 (646) 403-4525 marketing@hexaviewtech.com Follow Us

More Related