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.
this is a funny and clear way of explaining the k-means algorithm 😂 k-means clustering is a method of vector quantization that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. It's an unsupervised algorithm that devides your data into n classes, needing no ground truth at all. A new observation is classified following the nearest mean values of the clusters and the cluster's class is then attributed to the observation. posted on Instagram - https://instagr.am/p/CLt6A_8gRLh/
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.
Clustering in Machine Learning – Discover Hidden Patterns in Data
🎓 Welcome to Imarticus Learning! Ever wondered how machines group similar items together without being told what’s right or wrong? 🤖✨
That’s the magic of Clustering — an unsupervised learning technique that discovers hidden patterns in data. From customer segmentation to fraud detection, clustering helps businesses make smarter decisions every day.
In this video, we break down the fundamentals of clustering and show you the top algorithms used in real-world data science!
📌 What You’ll Learn
💡 Clustering 101 What clustering is — and when to use it.
📊 K-Means Clustering How centroids work + how to choose the right number of clusters.
📈 Hierarchical & DBSCAN Perfect for complex, irregular-shaped data.
🧠 Model Evaluation Silhouette score, elbow method & more expert techniques.
🌟 Why Learn with Imarticus Learning?
🔹 Expert mentors from leading tech and analytics industries 🔹 Flexible learning — designed for working professionals and fresh grads 🔹 Hands-on projects + placement prep + interview readiness 🔹 Career transformation with proven job-success support
🚀 Unlock High-Paying ML & AI Roles
Join the Postgraduate Program in Data Science and Analytics (PGA) — a 6-month, 100% job-assured program built for ambitious learners.
📈 Program Highlights: ✔ 2,000+ hiring partners ✔ 300+ learning hours ✔ 25+ real-world projects ✔ 10+ industry tools — Python, Tableau, Power BI & more ✔ ₹22.5 LPA highest salary | 52% avg salary hike
✨ Start your journey to becoming a Data Scientist today. Learn. Build. Get hired. Only with Imarticus Learning. 🔗
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!
Explainable AI for Digital Forensics #researchawards #fosawards #sciencefather
This work explores how unsupervised explainable AI can bridge critical knowledge gaps in digital forensics by uncovering hidden patterns, enhancing transparency, and supporting investigators with interpretable insights for evidence analysis.
Nomination Link: https://forensicscientist.org/award-nomination/?ecategory=Awards&rcategory=Awardee
Website: https://forensicscientist.org/
Contact🔍: [email protected]
