Lec-6.9:PREDICTIVE MODELING AND CAUSALITY| Can Data Predict the Future? 🤯|2ND YEAR COMPUTER SCIENCE

🎉 Chapter 6 – Final Lecture! ⬅️ Previous Lecture – 6.8:    • Lec-6.8:VALIDATION AND MODEL IMPROVEMENT| ...   ✅ You have reached the final lecture of this Chapter 6 series. If these lectures helped you, LIKE 👍 the video and SHARE it with your classmates so they can also prepare Chapter 6 easily. 📘 Welcome to KIMS College Official Channel Can we use past data to predict what might happen in the future? 🤔📊 In this lecture, we will learn about Predictive Modeling and Causality from Chapter 6: Data and Analysis for 2nd Year Computer Science students. You will understand the basic concept of Predictive Modeling and how data can be used to identify patterns and make predictions about future outcomes. We will also explore the concept of Causality and understand the difference between finding a relationship between variables and determining whether one factor actually causes a change in another. This topic is especially important for board exam preparation, MCQs, short questions, long questions, and conceptual understanding. The concepts are explained in simple and easy English with relevant examples to make this topic easier to understand. 📚 Chapter 6: Data and Analysis 📌 Topic: Predictive Modeling and Causality 🎓 Class: 2nd Year Computer Science Watch the complete lecture and strengthen your Data Science, Data Analysis, and Machine Learning concepts. 🔔 Subscribe to KIMS College Official Channel for complete Computer Science lectures and exam-focused preparation. 💬 Question: What is the difference between prediction and causation?