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[FreeCourseLab.com] Udemy - A-Z Machine Learning using Azure Machine Learning (AzureML)

Torrent Hash :
d2fa031514c1c61e679ba39c9ec91f2038d0622a
Content Size :
1.82 GB
Date :
2019-03-08
Short Magnet :
Short Magnet
https://0mag.biz/!o57V8q QR code
Files ( 225 )size
7. Regression Analysis/3. [Hands On] - Linear Regression model using OLS.mp491.03 MB
12. Text Analytics and Natural Language Processing/5. [Hands On] - Classify Customer Complaints using Text Analytics.mp490.99 MB
12. Text Analytics and Natural Language Processing/4. Feature Hashing.mp475.17 MB
1. Basics of Machine Learning/4. Why Machine Learning is the Future.mp468.72 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/9. [Hands On] - Fisher Based LDA - Experiment.mp461.14 MB
13. Thank You and Bonus Lecture/1. Way Forward.mp457 MB
12. Text Analytics and Natural Language Processing/2. Text Pre-Processing.mp454.61 MB
4. Classification/2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.mp452.21 MB
12. Text Analytics and Natural Language Processing/3. Bag Of Words and N-Gram Models for Text features.mp449.96 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/2. Pearson Correlation Coefficient.mp447.22 MB
12. Text Analytics and Natural Language Processing/1. What is Text Analytics or Natural Language Processing.mp440.7 MB
3. Data Processing/5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.mp438.91 MB
11. Recommendation System/5. [Hands On] - Restaurant Recommendation Experiment.mp436.18 MB
3. Data Processing/6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.mp435.52 MB
4. Classification/12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.mp435.1 MB
11. Recommendation System/1. What is a Recommendation System.mp434.97 MB
8. Clustering/2. [Hands On] - Cluster Analysis Experiment 1.mp430.92 MB
4. Classification/4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.mp429.42 MB
7. Regression Analysis/5. Gradient Descent.mp427.66 MB
3. Data Processing/4. [Hands On] -Data Transform - Add RowsColumns, Remove Duplicates, Select Columns.mp426.47 MB
4. Classification/10. [Hands On] Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction.mp425.17 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/8. Fisher Based LDA - Intuition.mp424.08 MB
8. Clustering/1. What is Cluster Analysis.mp422.38 MB
3. Data Processing/2. [Hands On] - Data Input-Output - Convert and Unpack.mp422.09 MB
5. Hyperparameter Tuning/1. [Hands On] - Tune Hyperparameter for Best Parameter Selection.mp421.92 MB
4. Classification/6. [Hands On] Logistic Regression - Build Multi-Class Wine Quality Prediction Model.mp419.67 MB
4. Classification/3. Logistic Regression - Understand Parameters and Their Impact.mp419.55 MB
1. Basics of Machine Learning/8. Types of Machine Learning Models - Classification, Regression, Clustering etc.mp419.04 MB
3. Data Processing/1. [Hands On] - Data Input-Output - Upload Data.mp418.57 MB
4. Classification/13. [Hands On] - Decision Tree - Multi Class Decision Forest IRIS Data.mp418.57 MB
1. Basics of Machine Learning/5. What is Machine Learning.mp418.5 MB
8. Clustering/3. [Hands On] - Cluster Analysis Experiment 2 - Score and Evaluate.mp418.37 MB
9. Data Processing - Solving Data Processing Challenges/5. [Hands On] - Outliers Treatment - Clip Values.mp417.65 MB
11. Recommendation System/6. Understanding the Matchbox Recommendation Results.mp417.44 MB
7. Regression Analysis/10. [Hands On] - Decision Tree - Experiment Boosted Decision Tree.mp417.28 MB
6. Deploy Webservice/3. [Hands On] - Use the Web Service - Example of Excel.mp416.58 MB
9. Data Processing - Solving Data Processing Challenges/7. [Hands On] - Clean Missing Data with MICE.mp415.91 MB
9. Data Processing - Solving Data Processing Challenges/9. [Hands On] - SMOTE.mp415.54 MB
11. Recommendation System/2. Data Preparation using Recommender Split.mp414.92 MB
11. Recommendation System/3. What is Matchbox Recommender and Train Matchbox Recommender.mp414.56 MB
4. Classification/7. Decision Tree - What is Decision Tree.mp414.34 MB
9. Data Processing - Solving Data Processing Challenges/8. SMOTE - Create New Synthetic Observations.mp414.21 MB
7. Regression Analysis/1. What is Linear Regression.mp414.03 MB
4. Classification/15. [Hands On] - SVM - Adult Census Income Prediction.mp413.83 MB
4. Classification/5. Logistic Regression - Model Selection and Impact Analysis.mp413.77 MB
1. Basics of Machine Learning/6. Understanding various aspects of data - Type, Variables, Category.mp413.61 MB
1. Basics of Machine Learning/7. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range.mp413.31 MB
2. Getting Started with Azure ML/5. Azure ML Experiment Workflow.mp413.22 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/6. [Hands On] - Comparison Experiment for Correlation Coefficients.mp413.19 MB
3. Data Processing/3. [Hands On] - Data Input-Output - Import Data.mp413.12 MB

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