Curriculum
- 10 Sections
- 130 Lessons
- 400 Days
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- Module 1 : Machine Learning is the Future8
- 1.1Course Overview2 Minutes
- 1.2Overview Of 1st Module1 Minute
- 1.3Download documents1 Minute
- 1.4Introduction To Machine Learning2 Minutes
- 1.5Difference Between Traditional Programming & Machine Learning Programming4 Minutes
- 1.6Machine Learning & Artificial Intelligence9 Minutes
- 1.7Machine Learning Workflow6 Minutes
- 1.8Further Study1 Minute
- Module 2 : Introducing R and RStudio6
- Module 3 : Data Processing18
- 3.1R Overview Of Module 33 Minutes
- 3.2R Data-Types6 Minutes
- 3.3R Data-Structure3 Minutes
- 3.4Using String2 Minutes
- 3.5Using Matrix2 Minutes
- 3.6Data Transformation1 Minute
- 3.7Work with Data Set5 Minutes
- 3.8How to Filter Data10 Minutes
- 3.9Data Arrange2 Minutes
- 3.10Data Selection4 Minutes
- 3.11Using Mutate Function3 Minutes
- 3.12Using Gather Function6 Minutes
- 3.13Date & Time Data1 Minute
- 3.14Using Formula Of Date & Time7 Minutes
- 3.15Arrange Date & Time4 Minutes
- 3.16Finding Date & Time4 Minutes
- 3.17Missing Data4 Minutes
- 3.18Further Study1 Minute
- Module 4 : Data Visualization13
- 4.1Overview Of Module 41 Minute
- 4.2R Basic Plot And Lattice Plot6 Minutes
- 4.3Ggplot2 Scatter Plot6 Minutes
- 4.4Example of Scatter Plot3 Minutes
- 4.5Dividing Data in Different Plot3 Minutes
- 4.6Geom Smooth Function4 Minutes
- 4.7Drawing Line & Bar Plot8 Minutes
- 4.8Inserting Variables Into Bar Plot2 Minutes
- 4.9Drawing Stacked Bar Chart3 Minutes
- 4.10Box Plot4 Minutes
- 4.11Polar Transformation1 Minute
- 4.12Histogram2 Minutes
- 4.13Further Study1 Minute
- Module 5: Essential Statistics11
- 5.1Overview Of Module 51 Minute
- 5.2Central Tendency3 Minutes
- 5.3Working With Central Tendency3 Minutes
- 5.4Working With Central Tendency 23 Minutes
- 5.5Working With Central Tendency 31 Minute
- 5.6Normal Curves3 Minutes
- 5.7Outliers And Quartiles3 Minutes
- 5.8Outliers And Quartiles Execution1 Minute
- 5.9P-Value2 Minutes
- 5.10Confusion Matrix3 Minutes
- 5.11Further Study2 Minutes
- Module 6 : Regression Analysis18
- 6.1Linear Regression3 Minutes
- 6.2Solving Problem of Regression Analysis6 Minutes
- 6.3Randomly Data Divide4 Minutes
- 6.4Simple Linear Regression4 Minutes
- 6.5Multiple Linear Regression5 Minutes
- 6.6Data Prediction5 Minutes
- 6.7Support Vector Regression(SVR)2 Minutes
- 6.8Working With Support Vector Regression5 Minutes
- 6.9Decision Tree Regression3 Minutes
- 6.10Using Algorithm With Decision Tree Regression3 Minutes
- 6.11Decision Tree Visualization4 Minutes
- 6.12Random Forest Regression1 Minute
- 6.13Working With Random Forest Regression4 Minutes
- 6.14Predicted Value2 Minutes
- 6.15Model Comparison2 Minutes
- 6.16View Smooth Carve1 Minute
- 6.17Predicting From Production Curve6 Minutes
- 6.18Further Study2 Minutes
- Module 7 : Classification Analysis19
- 7.1Overview Module 72 Minutes
- 7.2Review Data2 Minutes
- 7.3Data Coveting3 Minutes
- 7.4Divided Datasets Into Training & Test Datasets5 Minutes
- 7.5Applying Formula of Logistic Regression5 Minutes
- 7.6K-Nearest Neighbors(K-Nn) Classification1 Minute
- 7.7Working With K-Nearest Neighbors(K-Nn) Classification7 Minutes
- 7.8Support Vector Machines (SVM)1 Minute
- 7.9Working with Support Vector Machines Classification3 Minutes
- 7.10Calculating Ypred Value3 Minutes
- 7.11Naive Bayes Classification1 Minute
- 7.12Working with Naive Bayes Classification3 Minutes
- 7.13Decision Tree Classification1 Minute
- 7.14Working with Decision Tree Classification4 Minutes
- 7.15Decision Tree Visualization2 Minutes
- 7.16Random Forest Classification1 Minute
- 7.17Working with Random Forest Classification4 Minutes
- 7.18Apply Modelin Production Data7 Minutes
- 7.19Further Study1 Minute
- Module 8 : Clustering Analysis11
- 8.1Overview of Module 83 Minutes
- 8.2Working with Clustering Analysis3 Minutes
- 8.3K-Means Clustering2 Minutes
- 8.4Applying K-Means Clustering3 Minutes
- 8.5Visualize Clustering3 Minutes
- 8.6K-Means Clustering Visualization7 Minutes
- 8.7Hierarchical Clustering1 Minute
- 8.8Working with Hierarchical Clustering4 Minutes
- 8.9Cutree4 Minutes
- 8.10Hierarchical Clustering Visualization4 Minutes
- 8.11Further Study1 Minute
- Module 9 : Association Rule Learning & Time Series Analysis11
- 9.1Overview of Module 92 Minutes
- 9.2Association Rule of Learning4 Minutes
- 9.3Apriori Algorithm4 Minutes
- 9.4Eclat Algorithm3 Minutes
- 9.5Time Series Analysis1 Minute
- 9.6Creating Time Series Data5 Minutes
- 9.7Time Series Decomposition5 Minutes
- 9.8Subtracting Time Series Elements3 Minutes
- 9.9Exponential Smoothing3 Minutes
- 9.10Auto Regressive Integrated Moving Average3 Minutes
- 9.11Further Study1 Minute
- Module 10 : Advanced Machine Learning15
- 10.1Overview of Module 102 Minutes
- 10.2Natural Language Processing4 Minutes
- 10.3Row Data To Corpus2 Minutes
- 10.4Bag of Words Model3 Minutes
- 10.5Dividing Data To Training & Test Sets-13 Minutes
- 10.6Random Forest Prediction5 Minutes
- 10.7Deep Learning (Artificial Neural Network)2 Minutes
- 10.8Datasets3 Minutes
- 10.9Data Conversion1 Minute
- 10.10Divide Data Set3 Minutes
- 10.11Using H2o Deep Learning Model 12 Minutes
- 10.12Using H2o Deep Learning Model 24 Minutes
- 10.13Calculating Ypred Value5 Minutes
- 10.14Further Study2 Minutes
- 10.15Conclusion3 Minutes
Overview Of 1st Module
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