*Machine Learning notes ~are available on the Vidyari.com website.* *You can purchase them using the link below.* *Module 2 Notes :* https://www.vidyari.com/file/Machine-Learning-Module-2-Notes-(BCS602)-for-VTU-students-duf3l/6a1720ca6e06a40761303acb *Use coupon code: EDU YODHA to get 50% OFF on your purchase.* Machine learning BCS602 one shot|Machine learning|Module-1 one shot(complete Theory)MQP+PYQ|Eduyodha Follow the ENGINEERING IN KARNATAKA ✪ channel on WhatsApp: https://whatsapp.com/channel/0029Vb27q0JKwqSbZewkPh1r 🔥 BCA602 Machine Learning One Shot Video is Here! 🔥 0:00 Introduction 0:12:42 Gaussian Elimination Method & Row Echelon Form 0:19:31 LU Decomposition 0:30:08 Principal Component Analysis (PCA) 1:12:27 Find-S Algorithm 1:19:40 Singular Value Decomposition (SVD) 1:44:12 Candidate Elimination Algorithm 1:56:03 General-to-Specific Problem Solving In this complete Machine Learning one-shot session, we cover all important concepts, algorithms, theory questions, problem-solving methods, and exam-oriented explanations required for BCA602 VTU examinations. ✅ Complete Machine Learning Concepts ✅ Important Theory Questions ✅ Problem Solving & Numericals ✅ Easy Explanations for Exams ✅ Last Minute Revision ✅ VTU Exam Preparation Strategy ✅ Algorithms Explained with Examples This video is specially designed for: 🎯 BCA Students 🎯 VTU Students 🎯 Engineering & Degree Students 🎯 Beginners Learning Machine Learning 📌 Topics Covered: ✔ Introduction to Machine Learning ✔ Supervised Learning ✔ Unsupervised Learning ✔ Reinforcement Learning ✔ Classification & Regression ✔ Decision Trees ✔ K-Means Clustering ✔ Naive Bayes ✔ KNN Algorithm ✔ Q-Learning ✔ Machine Learning Problems & Numericals ✔ Important Exam Questions ✔ ML Applications & Advantages 🔥 Perfect for: BCA602 Machine Learning Exam Preparation VTU Machine Learning Important Questions Last Minute ML Revision Machine Learning One Shot Learning 📢 Subscribe to EDU YODHA for more exam-oriented videos, one-shot revisions, important questions, and placement guidance. #MachineLearning #BCA602 #VTU #MachineLearningOneShot #MLFullCourse #EDUYODHA #VTUExams #ImportantQuestions #MLRevision #MachineLearningVTU #MachineLearningConcepts #MLProblems #MachineLearningNumericals #MachineLearningForBeginners #BCA machine learning one shot bca602 machine learning machine learning vtu machine learning important questions machine learning numericals machine learning problems machine learning crash course machine learning full revision machine learning concepts explained bca machine learning machine learning for beginners machine learning complete course ml one shot revision machine learning exam preparation vtu machine learning one shot machine learning algorithms explained decision tree machine learning k means clustering explained q learning algorithm naive bayes explained supervised learning unsupervised learning reinforcement learning machine learning syllabus vtu bca602 important questions machine learning last minute revision machine learning full syllabus ml viva questions machine learning tutorial machine learning simplified machine learning notes machine learning theory and numericals machine learning exam questions machine learning Kannada machine learning English eduyodha machine learning edu yodha bca602 machine learning module wise machine learning marathon machine learning concepts and problems machine learning solved examples #MachineLearning #BCA602 #MachineLearningOneShot #MLOneShot #VTU #VTUExams #MachineLearningVTU #MLRevision #MachineLearningCourse #MachineLearningTutorial #MachineLearningForBeginners #MachineLearningConcepts #MachineLearningProblems #MachineLearningNumericals #DecisionTree #KMeansClustering #NaiveBayes #QLearning #SupervisedLearning #UnsupervisedLearning #ReinforcementLearning #MLAlgorithms #ImportantQuestions #ExamPreparation #LastMinuteRevision #CrashCourse #OneShotRevision #BCA #EngineeringStudents #VTUStudents #EDUYODHA #Education #StudySmart #AI #ArtificialIntelligence #DataScience #MLCourse #CollegeExams #VTUNotes #MachineLearningExam
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PCA is absolute nightmare 😅
Students, there is a small correction in the normalization step while finding the projection vector. The vector obtained was: v = (−3, −3) For normalization/simplification, we should divide by −3 (not by 3), because we usually divide by the common factor along with its sign to keep the direction mathematically consistent. So: (−3, −3) ÷ (−3) = (1, 1) In the video, I mistakenly divided by 3 instead of −3. Please make this correction while writing notes or preparing for exams. Please make sure ... You people notice and correct it .
1:28:36 -4.99
PCA AND SVD hit Hard 🤕
can u please upload the theory part one shot videos it wil be more useful for us pls,its my request can u plz upload .
1:24:01 not linear, it's quadratic equation
10:18 akka instead of solving manually for particularly find stand deviation of x and y can we do directly by calculator in a single line....will they remove marks for step ... i thought i will write formula and directly calc in calci and i will get direct ans fro stand x and y to calculate corelation
mam theory questions en odbeku mam...plz make one shot for theory also..
BCS502 Passing package for Cn I have exam on 29/5/26
Follow the ENGINEERING IN KARNATAKA ✪ channel on WhatsApp: /channel/0029Vb27q0JKwqSbZewkPh1r *Machine Learning notes ~are available on the Vidyari.com website.* *You can purchase them using the link below.* *Module 2 Notes :* /file/Machine-Learning-Module-2-Notes-(BCS602)-for-VTU-students-duf3l/6a1720ca6e06a40761303acb *Use coupon code: EDU YODHA to get 50% OFF on your purchase.*
Please teach in English as it is a common language for everybody,,,, we are unable to understand kannada 😢😢😢
Mam please upload vedios theory part of module 2,3,4,5
Mam in the 3rd q Gaussian elimination method you have taken 0x + 1y = 1 how can 0x will be valid
Mam please upload notes
Mam,,in SVD problem,the final answer is in the form of USV " ,,but u only wrote V instead of V transpose.( 1:43:52)
Mam in id3,c4.5, both method we need to solve or wht
27:51. Akka if one time we have changed the value from 0 to any number using the row operation then can we change it again if the number we get is higher in the identity matrix(L matrix). Ex:In R3 first column(1st number)has 3 as the value.Then if I get any number higher that 3 then can I can the number as u changed the number from 0 to 2/3 for the next number. Pls clear the doubt
candidate elimination ali obtain the complete version space a andre?
mam last problem in step 4 job offer is YES but u took as NO is it like tht only or a mistake
Mam candidate key elimination ali 4th row last colum ali yes ede neevu no antha hakidire