20:57

Capstone Sentiment Analysis Using Text Mining: A Real-World Data Science Project

33:03

Credit Scoring in Python Building a Complete Scorecard

24:31

MovieLens Data Analytics & Recommender Systems

14:38

1 - Fake News Detection with NLP and Transformers

19:45

4 - Insurance Claim Severity Prediction - Regression

16:47

3 - Healthcare Diabetes Prediction - Binary Classification

18:44

5 - House Price Prediction - Regression with Ames Dataset

13:17

4 - Loan Default Prediction - Risk Modeling

17:14

1 - Customer Churn Prediction - Classification Models

15:20

2 - Retail Sales Dashboard with Plotly and Streamlit

19:36

3 - COVID-19 Data Tracker using API and Time-Series Visualization

19:02

1 - Titanic Survival Analysis - EDA and ML Basics

26:20

5 Capstone Project: Comprehensive Data Mining Case Study Walkthrough

20:25

1 Customer Churn Prediction End-to-End Capstone Project

14:58

5. Can You Predict Stock Prices With Python?

18:55

3 What is EXPONENTIAL Smoothing in Time Series Forecasting?

18:46

2. How to Catch Outliers in Your Data Fast!

19:16

1 Introduction to Anomaly and Outlier Detection

22:04

6 Hands-on Project: Predicting Diabetes with Ensemble Models

23:00

4 Support Vector Machines (SVM): Fundamentals and Applications

16:37

3 Boosting Techniques: AdaBoost and XGBoost Explained

22:33

2 Bagging and Random Forests: Ensemble Methods for Advanced Machine Learning

16:02

6 Hands-on Clustering Project: Socio-Economic Segmentation Explained

15:04

5 Cluster Evaluation Metrics and Interpretation

20:35

4 Density-Based Clustering with DBSCAN

17:24

3 Hierarchical Clustering Techniques: Concepts and Examples

15:55

2 k-Means Clustering Algorithm Explained: Step-by-Step Guide

16:45

1 Introduction to Clustering in Machine Learning

19:20

6 ROC Curves, AUC, and Confusion Matrix Analysis for Classification Models

19:36

5 Evaluating Classifiers: Accuracy, Precision, Recall, and F1-Score Explained

21:26

2 Naive Bayes Classifier: Fundamentals and Applications

26:24

1 Decision Trees: ID3, C4.5, and CART Explained for Classification

17:14

4 Association Rule Mining with Apriori Algorithm

16:10

3 Visualization: Histograms, Scatterplots, and Heatmaps Explained

16:12

2 Summarization and Descriptive Statistics in Data Mining

25:17

1 Introduction to Exploratory Data Mining

13:17

5 Hands-on Preprocessing with Titanic and Iris Datasets

18:04

4 Data Integration and Feature Engineering in Data Preprocessing

22:12

3 Dimensionality Reduction with PCA: Concepts and Implementation

19:41

2 Data Transformation: Normalization, Encoding, and Feature Scaling Explained

17:20

1 Data Cleaning: Handling Missing Values, Noise, and Outliers

13:12

5 Exploratory Data Analysis and Visualization Basics

25:48

4 Getting Started with Python, Pandas, and scikit-learn

28:35

3 Applications of Data Mining in Business, Healthcare, and Security

21:57

1 Introduction to Data Mining and the KDD Process

34:30

5 - Capstone Project- Comprehensive Statistical Analysis Case Study

23:33

3 - Introduction to Bayesian Statistics- Priors and Posteriors

23:51

2 - Stationarity, ACF, PACF and ARIMA Basics

16:01

1 - Project- Simulating Dice Rolls and the Law of Large Numbers

29:28

4 - Project- Time Series Forecasting with Python

24:29

3 - Project- Regression Analysis for Business Data

19:08

2 - Project- Hypothesis Testing on Real-World Datasets

20:41

5 - Practical Bayesian Inference Examples

15:25

4 - Bayesian Estimation with SciPy and PyMC

24:35

1 - Python Jupyter Notebook Setup for Probability and Statistics

12:38

1 - Covariance and Correlation- Pearson and Spearman

11:20

4 - Random Number Generation with NumPy

16:47

3 - Monte Carlo Simulations in Python

12:27

4 - Hypothesis Testing- Concepts, Errors, p-values

24:18

3 - Bayes Theorem with Real-Life Examples