Download Udemy - Master Machine Learning with Practical Case Studies torrent

Udemy - Master Machine Learning with Practical Case Studies

Torrent:	Udemy - Master Machine Learning with Practical Case Studies
Description:	Master Machine Learning with Practical Case Studies https://DevCourseWeb.com Published 8/2024 MP4 \| Video: h264, 1280x720 \| Audio: AAC, 44.1 KHz, 2 Ch Language: English \| Duration: 6h 36m \| Size: 2.93 GB Hands on Machine Learning with Algorithms and Case Studies using different Datasets What you'll learn How to use Machine Learning Model for making Predictions for Real Life Problems Understand Machine Learning to Apply in Real Practical Scenarios Master Machine Learning techniques Develop Insights for Data Wrangling, Data Cleansing, Data Enrichment, Data Analytics using Machine Learning Build Linear Regression Model Build Logistic Regression Model Build Decision Tree Model Understand ARIMA Implement KMeans Clustering Implement Naive Bayes Understand Boosting Algorithms Build XGBRegressor Model Requirements No prior Programming Experience required.
Downloads:	44
Category:	Other /Tutorials
Size:	2.9 GB
Show Files »	[ DevCourseWeb.com ] Udemy - Master Machine Learning with Practical Case Studies Get Bonus Downloads Here.url (0.2 KB) ~Get Your Files Here ! 1 - Linear Regression using House Rent Prediction 1 - 1 - Introduction to Linear Regression.mp4.mp4 (59.1 MB) 10 - 10 - Tabulate Results.mov.mp4 (12.5 MB) 2 - 2 - Linear Regression.mov.mp4 (27.1 MB) 3 - 3 - Import Data.mov.mp4 (34.4 MB) 4 - 4 -Outlier Function.mov.mp4 (23.0 MB) 5 - 5 - Visualization.mov.mp4 (33.9 MB) 6 - 6 - Encode Data.mov.mp4 (30.4 MB) 7 - 7 - Linear Model.mov.mp4 (26.9 MB) 8 - 8 - Cross Validation and RMSE.mov.mp4 (10.1 MB) 9 - 9 - Plot Predictions.mov.mp4 (28.9 MB) House_Rent_Dataset.csv.csv (553.7 KB) 10 - Naive Bayes using Fraud Classification 1 - 1 - Introduction.mov.mp4 (39.1 MB) 2 - 2 - Load Dataset.mov.mp4 (30.0 MB) 2 - 3 - EDA.mov.mp4 (47.1 MB) 3 - 4 - Modeling.mov.mp4 (26.8 MB) 4 - 5 - Results.mov.mp4 (6.1 MB) 11 - AdaBoost using Housing Price Prediction 1 - 1 - Load Dataset.mov.mp4 (74.7 MB) 2 - 2 - EDA.mov.mp4 (45.0 MB) 3 - 3 - Modeling and Prediction.mov.mp4 (76.7 MB) house_pricing_data.csv.csv (2.4 MB) 12 - ARIMA 1 - 1 - Introduction Part 1.mov.mp4 (16.6 MB) 2 - 2 - Introduction Part 2.mov.mp4 (54.3 MB) 3 - 3 - Stationarity Checks.mov.mp4 (16.4 MB) 4 - 4 - Seasonal Decomposition Part 1.mov.mp4 (20.6 MB) 5 - 5 - Seasonal Decomposition Part 2.mov.mp4 (43.1 MB) 6 - 6 - Modeling and Prediction.mov.mp4 (41.8 MB) 13 - XGB using Stock Dataset 1 - 1 - Introduction.mov.mp4 (46.3 MB) 2 - 2 - EDA.mov.mp4 (29.7 MB) 3 - 3 - Data Preparation.mov.mp4 (42.8 MB) 4 - 4 - Modeling.mov.mp4 (84.7 MB) 5 - 5 - Backtesting.mov.mp4 (38.0 MB) 6 - 6 - Results.mov.mp4 (29.8 MB) 2 - Multicollinearity using Car Dataset 1 - 1 - Introduction.mp4.mp4 (57.5 MB) 2 - 2 - Linear Regression Data.mov.mp4 (28.4 MB) 3 - 3 - EDA Part 1.mov.mp4 (44.1 MB) 4 - 4 - EDA Part 2.mov.mp4 (50.6 MB) 5 - 5 - EDA Part 3.mov.mp4 (14.0 MB) 6 - 6 - Variance Inflation Factor.mov.mp4 (28.2 MB) 7 - 7 - Predictions.mov.mp4 (78.6 MB) Car_data.csv.csv (219.8 KB) 3 - Logistic Regression using Credit Card Fraud Classification 1 - 1 - Introduction.mov.mp4 (126.6 MB) 2 - 2 - Logistic Regression.mp4.mp4 (41.2 MB) 3 - 3 - EDA Part 1.mov.mp4 (35.7 MB) 3 - 4 - EDA Part 2.mov.mp4 (33.1 MB) 4 - 5 - Data Scaling Part 1.mov.mp4 (16.3 MB) 5 - 6 - Data Scaling Part 2.mov.mp4 (45.8 MB) 6 - 7 - Outlier Visualization.mov.mp4 (129.2 MB) 7 - 8 - Predictions.mov.mp4 (42.5 MB) 8 - 9 - Finding Best Parameters.mov.mp4 (33.4 MB) 4 - SVC using Bank Customer Retirement Classification 1 - 1 - SVC.mov.mp4 (44.5 MB) Bank_Customer_retirement.csv.csv (14.9 KB) 5 - Regularization using Sales Price Dataset 1 - 1 - Regularization Part 1.mov.mp4 (89.5 MB) 2 - 2 - Regularization Part 2.mov.mp4 (67.4 MB) test.csv.csv (440.8 KB) train.csv.csv (449.9 KB) 6 - Decision Tree 1 - 1 - EDA.mov.mp4 (63.8 MB) 2 - 2 - Model Predictions.mov.mp4 (97.4 MB) 7 - Random Forest using Housing Price Dataset 1 - 1 - Introduction to Random Forest.mp4.mp4 (106.8 MB) 10 - 10 - Comparison.mov.mp4 (13.7 MB) 2 - 2 - Overview.mov.mp4 (11.9 MB) 3 - 3 - Import Dataset.mov.mp4 (39.6 MB) 4 - 4 - Metrics.mov.mp4 (9.2 MB) 5 - 5 - Working of Random Forest.mov.mp4 (24.8 MB) 6 - 6 - Linear Regression Modeling.mov.mp4 (52.3 MB) 7 - 7 - Linear Regression Predictions.mov.mp4 (26.0 MB) 8 - 8 - Random Forest Modeling.mov.mp4 (26.3 MB) 9 - 9 - Random Forest Predictions.mov.mp4 (19.2 MB) USA_Housing.csv.csv (709.2 KB) 8 - PCA using Housing Price Prediction 1 - 1 - Part 1.mov.mp4 (98.7 MB) 2 - 2 - Part 2.mov.mp4 (85.7 MB) test.csv.csv (440.8 KB) train.csv.csv (449.9 KB) 9 - K-Means using Social Media and Customer Segmentation 1 - 1 - KMeans using Social Media Dataset Part 1.mov.mp4 (90.3 MB) 2 - 2 - KMeans using Social Media Dataset Part 2.mov.mp4 (39.4 MB) 3 - 3 - KMeans using Mall Customer Segmentation Part 1.mov.mp4 (65.7 MB) 4 - 4 - KMeans using Mall Customer Segmentation Part 2.mov.mp4 (22.5 MB) Live.csv.csv (553.8 KB) Mall_Customers.csv.csv (3.9 KB) Bonus Resources.txt (0.4 KB) files
Added:	2024-09-19 23:09:33
Language:	English
Peers:	Seeders : 7 , Leechers : 30
Tags:	Development Data Science Udemy
Release name:	Udemy - Master Machine Learning with Practical Case Studies
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