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[ DevCourseWeb com ] Udemy - Master Machine Learning with Practical Case Studies
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Get Bonus Downloads Here.url (Size: 2.93 GB) (Files: 80)
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1 - Linear Regression using House Rent Prediction
1 - 1 - Introduction to Linear Regression.mp4.mp4
10 - 10 - Tabulate Results.mov.mp4
2 - 2 - Linear Regression.mov.mp4
3 - 3 - Import Data.mov.mp4
4 - 4 -Outlier Function.mov.mp4
5 - 5 - Visualization.mov.mp4
6 - 6 - Encode Data.mov.mp4
7 - 7 - Linear Model.mov.mp4
8 - 8 - Cross Validation and RMSE.mov.mp4
9 - 9 - Plot Predictions.mov.mp4
House_Rent_Dataset.csv.csv
10 - Naive Bayes using Fraud Classification
1 - 1 - Introduction.mov.mp4
2 - 2 - Load Dataset.mov.mp4
2 - 3 - EDA.mov.mp4
3 - 4 - Modeling.mov.mp4
4 - 5 - Results.mov.mp4
11 - AdaBoost using Housing Price Prediction
1 - 1 - Load Dataset.mov.mp4
2 - 2 - EDA.mov.mp4
3 - 3 - Modeling and Prediction.mov.mp4
house_pricing_data.csv.csv
12 - ARIMA
1 - 1 - Introduction Part 1.mov.mp4
2 - 2 - Introduction Part 2.mov.mp4
3 - 3 - Stationarity Checks.mov.mp4
4 - 4 - Seasonal Decomposition Part 1.mov.mp4
5 - 5 - Seasonal Decomposition Part 2.mov.mp4
6 - 6 - Modeling and Prediction.mov.mp4
13 - XGB using Stock Dataset
1 - 1 - Introduction.mov.mp4
2 - 2 - EDA.mov.mp4
3 - 3 - Data Preparation.mov.mp4
4 - 4 - Modeling.mov.mp4
5 - 5 - Backtesting.mov.mp4
6 - 6 - Results.mov.mp4
2 - Multicollinearity using Car Dataset
1 - 1 - Introduction.mp4.mp4
2 - 2 - Linear Regression Data.mov.mp4
3 - 3 - EDA Part 1.mov.mp4
4 - 4 - EDA Part 2.mov.mp4
5 - 5 - EDA Part 3.mov.mp4
6 - 6 - Variance Inflation Factor.mov.mp4
7 - 7 - Predictions.mov.mp4
Car_data.csv.csv
3 - Logistic Regression using Credit Card Fraud Classification
1 - 1 - Introduction.mov.mp4
2 - 2 - Logistic Regression.mp4.mp4
3 - 3 - EDA Part 1.mov.mp4
3 - 4 - EDA Part 2.mov.mp4
4 - 5 - Data Scaling Part 1.mov.mp4
5 - 6 - Data Scaling Part 2.mov.mp4
6 - 7 - Outlier Visualization.mov.mp4
7 - 8 - Predictions.mov.mp4
8 - 9 - Finding Best Parameters.mov.mp4
4 - SVC using Bank Customer Retirement Classification
1 - 1 - SVC.mov.mp4
Bank_Customer_retirement.csv.csv
5 - Regularization using Sales Price Dataset
1 - 1 - Regularization Part 1.mov.mp4
2 - 2 - Regularization Part 2.mov.mp4
test.csv.csv
train.csv.csv
6 - Decision Tree
1 - 1 - EDA.mov.mp4
2 - 2 - Model Predictions.mov.mp4
7 - Random Forest using Housing Price Dataset
1 - 1 - Introduction to Random Forest.mp4.mp4
10 - 10 - Comparison.mov.mp4
2 - 2 - Overview.mov.mp4
3 - 3 - Import Dataset.mov.mp4
4 - 4 - Metrics.mov.mp4
5 - 5 - Working of Random Forest.mov.mp4
6 - 6 - Linear Regression Modeling.mov.mp4
7 - 7 - Linear Regression Predictions.mov.mp4
8 - 8 - Random Forest Modeling.mov.mp4
9 - 9 - Random Forest Predictions.mov.mp4
USA_Housing.csv.csv
8 - PCA using Housing Price Prediction
1 - 1 - Part 1.mov.mp4
2 - 2 - Part 2.mov.mp4
test.csv.csv
train.csv.csv
9 - K-Means using Social Media and Customer Segmentation
1 - 1 - KMeans using Social Media Dataset Part 1.mov.mp4
2 - 2 - KMeans using Social Media Dataset Part 2.mov.mp4
3 - 3 - KMeans using Mall Customer Segmentation Part 1.mov.mp4
4 - 4 - KMeans using Mall Customer Segmentation Part 2.mov.mp4
Live.csv.csv
Mall_Customers.csv.csv
Bonus Resources.txt
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