Скачать или смотреть CLUSTERING | Unsupervised | Machine Learning | Gate DA | Lec : 12 | Gyana Sir

ML Lecture : 01 :    • Machine Learning | Introduction| Syllabus ...  
ML Lecture : 02 :    • Supervised Learning | Linear Regression | ...  
ML Lecture : 03 :    • Cost Function | Regularization | R-Squared...  
ML Lecture : 04 :    • Regression Concept | Performance Metrics |...  
ML Lecture : 05 :    • Decision Tree Algorithm | Gate DA | Lec : ...  
ML Lecture : 06 :    • Cross Validation | Gate DA | Lec : 06 | Gy...  
ML Lecture : 07 :    • Feature Scaling | Naive Baye's Algorithm |...  
ML Lecture : 08 :    • Ensemble method | Machine Learning | Gate ...  
ML Lecture : 09:    • Random Forest | Bagging Technique | Machin...  
ML Lecture : 10:    • KNN | Bagging Technique | Machine Learning...  
ML Lecture : 11:    • Bias & Variance Trade Off | Machine Learni...  

AI Lecture : 01 :    • Artificial Intelligence | Introduction| Sy...  

In this Video Series We are Discuss all about Machine Learning Syllabus:
(i) Supervised Learning: regression and classification problems, simple linear
regression, multiple linear regression, ridge regression, logistic regression, k-nearest neighbor, naive
Bayes classifier, linear discriminant analysis, support vector machine, decision trees, bias-variance
trade-off, cross-validation methods such as leave-one-out (LOO) cross-validation, k-folds cross validation, multi-layer perceptron, feed-forward neural network; (ii) Unsupervised Learning: clustering
algorithms, k-means/k-medoid, hierarchical clustering, top-down, bottom-up: single-linkage, multiple linkage, dimensionality reduction, principal component analysis.

NumPy Complete Playlist :
   • Numpy complete course  

WhatsApp Link For Doubt and Notes:
https://chat.whatsapp.com/CEr6zRf8ZxT...

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