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Introduction

AI Vs ML vs DL vs Data Science

Machine LEarning and Deep Learning

Regression And Classification

Linear Regression Algorithm

Ridge And Lasso Regression Algorithms

Logistic Regression Algorithm

Linear Regression Practical Implementation

Ridge And Lasso Regression Practical Implementation

Naive Baye's Algorithms

KNN Algorithm Intuition

Decision Tree Classification Algorithms

Decision Tree Regression Algorithms

Practical Implementation Of Deicsion Tree Classifier

Ensemble Bagging And Bossting Techniques

Random Forest Classifier And Regressor

Boosting, Adaboost Machine Learning Algorithms

K Means Clustering Algorithm

Hierarichal Clustering Algorithms

Silhoutte Clustering- Validating Clusters

Dbscan Clustering Algorithms

Clustering Practical Examples

Bias And Variance Algorithms

Xgboost Classifier Algorithms

Xgboost Regressor Algorithms

SVM Algorithm Machine LEarning Algorithm

Description:

Embark on a comprehensive 6-hour journey through the world of machine learning with this in-depth tutorial. Explore the distinctions between AI, ML, DL, and Data Science before diving into core concepts like regression and classification. Master essential algorithms including Linear Regression, Ridge and Lasso Regression, Logistic Regression, Naive Bayes, KNN, Decision Trees, and ensemble methods. Gain practical implementation skills through hands-on examples. Delve into clustering techniques such as K-Means, Hierarchical, and DBSCAN. Understand crucial concepts like bias and variance. Conclude with advanced topics including XGBoost and SVM algorithms. Access supplementary materials and data science blogs for further learning.

Complete Machine Learning in 6 Hours - Krish Naik

Krish Naik

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#Computer Science #Machine Learning #Deep Learning #Mathematics #Statistics & Probability #Linear Regression #Classification #Logistic Regression #Decision Trees #Clustering #Random Forests

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