Jul 17, 2024
Machine learning algorithms use data to make predictions and decisions without explicit programming, enabling automation and insights for various applications like healthcare and finance.
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Machine learning algorithms use data to make predictions and decisions without explicit programming, enabling automation and insights for various applications like healthcare and finance.
Understanding Supervised and Unsupervised Machine Learning
Machine learning is an advanced technology that enables computers to learn from large amounts of data and make intelligent decisions without human intervention. Organizations use various machine learning models to analyze complex data and create insights to enable more intelligent business decisions.
The most common form of machine learning is known as supervised machine learning. In this form of machine learning, a data scientist trains various algorithms on complex data. Common algorithms used in this form of machine learning include linear regression, logistic regression, multi-class classification, and support vector machines.
On the other hand, unsupervised machine learning works with unlabeled data. It allows organizations to identify complex patterns using various algorithms such as k-means clustering, principal component analysis, and association rules.
As organizations increasingly adopt AI technologies, data mining, and machine learning technologies, they enable themselves to make decisions on complex data to improve efficiency and innovation.
We provide customized and personalized solutions for all sizes of companies and all industry sectors.
지도학습, 비지도학습, 강화학습 완벽 정리! 스팸 필터부터 알파고까지, AI가 데이터로 배우는 3가지 방법을 실생활 예시로 쉽게 설명. 분류·회귀·군집화·보상 시스템의 모든 것. #AI학습 #Kmeans #ReinforcementLearning #SupervisedLearning #UnsupervisedLearning #강화학습 #고객세분화 #군집화 #머신러닝 #분류 #비지도학습 #스팸필터 #알파고 #자율주행 #지도학습 #집값예측 #추천시스템 #회귀 Read the full article
🚀 Understanding Types of Machine Learning | Imarticus Learning
Welcome to Imarticus Learning! 🌟 Machine Learning is revolutionizing industries — but do you really know how different types of ML work?
In this Part 1 video, we break down the three main types of Machine Learning — 👉 Supervised 👉 Unsupervised 👉 Reinforcement Learning
All explained with real-world examples so you can easily connect the concepts to practical applications!
📌 What You’ll Learn
💡 Introduction to Machine Learning – How ML models learn from data to make predictions.
📊 Supervised Learning – How labeled data trains models for classification and regression tasks.
📈 Unsupervised Learning – How ML uncovers hidden patterns and structures in unlabeled data.
🎯 Real-World Examples: ✔ Fraud detection in banking (Supervised) ✔ Customer segmentation in marketing (Unsupervised) ✔ How AI learns to play chess (Reinforcement Learning Preview)
💼 Why Learn with Imarticus Learning?
📘 Expert Mentors: Learn directly from industry professionals. 🧭 Flexible Learning: Study at your own pace with guided structure. 🧠 Comprehensive Support: Mock tests, expert mentorship, and curated materials. 🚀 Career Success: Turn your learning into real growth and job opportunities.
🎓 Fast-Track Your ML Career
Our Postgraduate Program in Data Science and Analytics (PGA) is a 6-month course designed for graduates and professionals with up to 3 years of experience.
💥 100% Job Assurance 💥 2,000+ Hiring Partners 💥 300+ Learning Hours & 25+ Projects 💥 Training in 10+ Tools – Python, Power BI, Tableau & more 💥 Up to 22.5 LPA Highest Salary | 52% Average Salary Hikes
Become job-ready for the future of data-driven innovation.
🎯 Ready to build your ML career? 👉 Visit imarticus.org to learn more and enroll today!
