Why Classification Accuracy Can Be Misleading in ML

Saw this graphic recently, and it just clicked. Probably the simplest, clearest explanation of Machine Learning I’ve come across. Instead of writing complex rules to solve problems, ML flips the script. We use data and known answers to learn the rules automatically. It changes the game for problems that are just too hard to code by hand. #MachineLearning #AI #DataScience #ArtificialIntelligence #Learning

🚀 Just published a new video: What is Machine Learning? If you’ve been curious about how Machine Learning works and want to start your journey step by step, this video is the perfect starting point. 🎥✨ 👉 Check it out https://lnkd.in/e8PCvR5m and let me know your thoughts! #MachineLearning #AI #ArtificialIntelligence #TechForBeginners #LearningJourney

"Machine Learning Explained Simply" Today I learned what Machine Learning really means! 📊 It’s when computers learn from examples instead of instructions. Just like humans learn from experience, AI learns from data. The concept sounds simple, but it’s incredibly powerful 🔥 #MachineLearning #AI

Meta-learning is such an interesting concept, this diagram shows how it actually works behind the scenes. Instead of starting from zero every time, the system uses knowledge from previous datasets and algorithms to suggest or rank the best models for new problems. 𝐈𝐧 𝐬𝐡𝐨𝐫𝐭, 𝐢𝐭’𝐬 𝐥𝐢𝐤𝐞 𝐠𝐢𝐯𝐢𝐧𝐠 𝐦𝐚𝐜𝐡𝐢𝐧𝐞 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐚 𝐦𝐞𝐦𝐨𝐫𝐲 — 𝐬𝐨 𝐢𝐭 𝐜𝐚𝐧 𝐥𝐞𝐚𝐫𝐧 𝐟𝐚𝐬𝐭𝐞𝐫 𝐚𝐧𝐝 𝐦𝐚𝐤𝐞 𝐬𝐦𝐚𝐫𝐭𝐞𝐫 𝐜𝐡𝐨𝐢𝐜𝐞𝐬 𝐨𝐯𝐞𝐫 𝐭𝐢𝐦𝐞. #MachineLearning #MetaLearning #AI #DataScience

Think data science is all about AI, Deep Learning, or "fancy models"? Think again. Even the most sophisticated algorithms rely on clean data, meaningful metrics, and structured experiments. True impact emerges when data guides decisions, uncovers actionable insights, and drives measurable results. AI and advanced models are powerful tools, but real value comes from turning insights into action. #datascience #businessstrategy #ai #ml #analytics #datadriven

Improving model accuracy isn’t just about choosing the right algorithm — it’s about evaluating it the right way. In this short video, we explain how k-fold cross-validation helps build more robust and reliable machine learning models, by ensuring that your data is used effectively for both training and testing. 🎥 Watch here: https://lnkd.in/dDhJyrmZ #MachineLearning #DataScience #AI #ModelEvaluation #ML

Machine learning isn’t just for big tech. DevDec uses ML models to help businesses predict, optimize, and make smarter decisions. Let’s build the future together: https://devdec.ca #MachineLearning #AI #DataDriven #AppDevelopment #Innovation #DevDec

🌟 New Blog Just Published! 🌟 📌 Master Self-Supervised Learning with Lightly AI 🚀 ✍️ Author: Hiren Dave 📖 Self-supervised learning has shifted from academic curiosity to a production-grade tool that directly attacks the data-label bottleneck. In practice, each additional annotated sample can cost dozens..... 🕒 Published: 2025-10-12 📂 Category: AI/ML 🔗 Read more: https://lnkd.in/djSaCT23 🚀✨ #selfsupervisedlear #lightlyai #unlabeleddata

🚀 Today’s Learning: Embeddings in AI While exploring AI concepts, I learned how embeddings make large documents (like PDFs) searchable and efficient to query. Here’s the process I understood: 1️⃣ Convert the document into text and break it into smaller, meaningful chunks. 2️⃣ Generate embeddings (vector representations) for each chunk using an embedding model. 3️⃣ Store these embeddings in a vector database. 4️⃣ When a query comes in, convert it into an embedding, search for the most relevant chunks, and send only those to the model. ✨ Why this is powerful: 1) Reduces token usage 2) Lowers cost and improves speed 3) Provides more accurate, context-aware answers I also created a small flow diagram to visualize why we choose embeddings: 🔗 https://lnkd.in/eq6ZGkHb Excited to keep exploring how embeddings and RAG pipelines can be applied in different domains! #AI #MachineLearning #Embeddings #RAG #LearningJourney

🤖 AI vs Machine Learning – Are They the Same? When we hear Artificial Intelligence, most of us immediately think of Machine Learning. But here’s the truth 👉 ML is just a subset of AI. In my latest blog, I break down: 🔹 What exactly is AI? 🔹 What exactly is ML? 🔹 Simple examples you already use daily 🔹 A table of key differences (goals, scope, examples) 🔹 An easy analogy to remember forever 🌊 If you’re starting your Agentic AI learning journey, this is step 1: get clarity between AI & ML. 📖 Read the full article here: https://lnkd.in/gXH_6jAM #AI #MachineLearning #AgenticAI #DataEngineering #LearningJourney #Biochemithon #blogging