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ML and Data Science

Track :

Computer Science

Lessons no : 38

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Lessons | 38

Lec 1 Introduction to Data Science ML Roadmap to Learn Data Science ML

Lec 1 Introduction to Data Science ML Roadmap to Learn Data Science ML

Lec 2 Supervised Learning Algorithms Machine Learning

Lec 2 Supervised Learning Algorithms Machine Learning

Lec 3 Introduction to Regression with Real Life Examples

Lec 3 Introduction to Regression with Real Life Examples

Lec 4 Linear Regression with Real life examples Calculations Easiest Explanation

Lec 4 Linear Regression with Real life examples Calculations Easiest Explanation

Lec 5 Logistic Regression with Simplest Easiest Example Machine Learning

Lec 5 Logistic Regression with Simplest Easiest Example Machine Learning

Lec 6 Linear Regression Vs Logistic Regression Supervised Learning Machine Learning

Lec 6 Linear Regression Vs Logistic Regression Supervised Learning Machine Learning

Lec 7 kNN Classification with Real Life Example Movie Imdb Example Supervised Learning

Lec 7 kNN Classification with Real Life Example Movie Imdb Example Supervised Learning

Lec 8 Naive Bayes Classification Full Explanation with examples Supervised Learning

Lec 8 Naive Bayes Classification Full Explanation with examples Supervised Learning

Lec 9 Introduction to Decision Tree with Real life examples

Lec 9 Introduction to Decision Tree with Real life examples

Lec 10 Decision Tree ID3 Algorithm with Example Calculations

Lec 10 Decision Tree ID3 Algorithm with Example Calculations

Conditional Probability with Easiest Explanation Example

Conditional Probability with Easiest Explanation Example

Introduction to Ensemble Learning with Real Life Examples Machine Learning

Introduction to Ensemble Learning with Real Life Examples Machine Learning

K mean Clustering with Numerical Example Unsupervised Learning Machine Learning

K mean Clustering with Numerical Example Unsupervised Learning Machine Learning

Hierarchical Clustering Agglomerative vs Divisive with examples

Hierarchical Clustering Agglomerative vs Divisive with examples

Single Linkage Clustering Agglomerative Clustering Hierarchical Clustering

Single Linkage Clustering Agglomerative Clustering Hierarchical Clustering

Complete Linkage Clustering with Example Clustering in Unsupervised Learning ML

Complete Linkage Clustering with Example Clustering in Unsupervised Learning ML

K medoids Clustering with Numerical Example Machine Learning

K medoids Clustering with Numerical Example Machine Learning

Random Forest in Machine Learning

Random Forest in Machine Learning

kNN for Classified Regression with Easiest Explanation Machine Learning

kNN for Classified Regression with Easiest Explanation Machine Learning

Mean Median Mode with Real Life examples Machine Learning

Mean Median Mode with Real Life examples Machine Learning

Standard Deviation Variance with Examples

Standard Deviation Variance with Examples

Bagging Bootstrap Aggregating in Machine Learning with examples

Bagging Bootstrap Aggregating in Machine Learning with examples

Supervised vs Unsupervised learning with real life example

Supervised vs Unsupervised learning with real life example

Python code for Mean Median Mode SD Variance and Range

Python code for Mean Median Mode SD Variance and Range

How Weights are Increased in Boosting Ensemble Learning

How Weights are Increased in Boosting Ensemble Learning

BAGGING vs BOOSTING vs STACKING in Ensemble Learning Machine Learning

BAGGING vs BOOSTING vs STACKING in Ensemble Learning Machine Learning

Bayes Theorem Total Probability with Examples

Bayes Theorem Total Probability with Examples

Cross Validation in Machine Learning with Examples

Cross Validation in Machine Learning with Examples

Pearson s Correlation Coefficient Supervised Learning Data Science Machine Learning

Pearson s Correlation Coefficient Supervised Learning Data Science Machine Learning

kNN k Nearest Neighbour Numerical Example Supervised Learning Machine Learning

kNN k Nearest Neighbour Numerical Example Supervised Learning Machine Learning

Decision Tree Example Calculate Entropy Information Gain Supervised Learning

Decision Tree Example Calculate Entropy Information Gain Supervised Learning

Single Linkage Clustering Example Unsupervised Learning Machine Learning

Single Linkage Clustering Example Unsupervised Learning Machine Learning

Token Parameters in LLama3 META Models 8B 70B Parameters Model GPT model

Token Parameters in LLama3 META Models 8B 70B Parameters Model GPT model

What is Data Preprocessing Data Cleaning Various Techniques with Example

What is Data Preprocessing Data Cleaning Various Techniques with Example

How to Deal with Missing Values in DataSet Data Preprocessing Data Cleaning Imputation Methods

How to Deal with Missing Values in DataSet Data Preprocessing Data Cleaning Imputation Methods

kNN Imputation with Examples Data Preprocessing and Data Cleaning

kNN Imputation with Examples Data Preprocessing and Data Cleaning

Fit Transform Method Data Preprocessing Machine Learning

Fit Transform Method Data Preprocessing Machine Learning

Feature Extraction in Data preprocessing Machine Learning

Feature Extraction in Data preprocessing Machine Learning

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Supervised Learning algorithms , in this course provides a comprehensive introduction to supervised learning algorithms, a core area of machine learning. You’ll explore key concepts, including how models are trained on labeled data to predict outcomes for new inputs. The course covers popular algorithms such as Linear Regression, Logistic Regression, Decision Trees, Support Vector Machines (SVM), Random Forest, K-Nearest Neighbors (KNN), and Gradient Boosting methods like XGBoost. Learn how to solve classification and regression problems, evaluate model performance using metrics, and optimize hyperparameters. With practical examples and case studies, this course equips you with the skills to apply supervised learning techniques to real-world tasks such as fraud detection, healthcare analytics, and predictive modeling.