Session 1 - SL Classification
Session 2 - Supervised Learning
Session 3 - Unsupervised Learning
Session 4 - Principal Components Analysis
Session 5 - Linear Discriminant Analysis
Session 6 - K - Fold
Session 7 - Boosting Machine Learning
Session 8 - One Hot Encoding
Session 9 - Time Series
Session 10 - Time Series LSTM
Session 11 - Sales Analysis
Session 12 - Case Studies
Assignment
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Assignment - Association Rule Recommendation System
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Assignment - Boosting
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Assignment - Classification
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Assignment - K Fold Cross validation Method
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Assignment - Linear Discriminant Analysis (LDA)
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Assignment - Principal Component Analysis
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Assignment - Time Series
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Assignment - Unsupervised Learning - Hierarchical Clustering
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Assignment - Unsupervised Learning - K Means Clustering
Assesment
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Assessment - Additional Components - Configuration and Hands on Tensor flow Basics
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Assessment - Additional Components - Dimensionality Reduction
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Assessment - Additional Components - End to End example for Regression
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Assessment - Association Rule Recommendation System
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Assessment - Boosting
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Assessment - Classification Models - Consolidated Model
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Assessment - Classification Models - Decision Tree
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Assessment - Classification Models - Logistic Regression
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Assessment - Classification Models - Naive Bayes Algorithm
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Assessment - Classification Models - Random Forest
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Assessment - Classification Models - Support Vector Machine Algorithm
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Assessment - Classification
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Assessment - Hadoop
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Assessment - K Fold Cross Validation Method
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Assessment - Linear Discriminant Analysis
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Assessment - Principal Component Analysis
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Assessment - Python to Excel Tools
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Assessment - Spark
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Assessment - Time Series
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Assessment - Unsupervised Learning - Hierarchical Clustering
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Assessment - Unsupervised Learning - K Means Clustering
Projects
PPTs
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Module 1 - SL Classification 1
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Module 1 - SL Classification 2
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Module 2 - Unsupervised Learning
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Module 3 - Principal Component Analysis - Part - C
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Module 3 - Principal Component Analysis - Part - A
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Module 3 - Principal Component Analysis - Part - B
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Module 4 - Linear Discriminant Analysis
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Module 5 - Boosting - Part B
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Module 5 - K-Fold - Part A
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Module 6 - Association Rule
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Module 6 - Building a Recommender System
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Module 7 - Time Series - ARIMA
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Module 7 - Time Series - LSTM
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Module 7 - Time Series - Part A
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Module 7 - Time Series - Part B
Datasets
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adult.csv
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Bank Data Dimension Reduction.csv
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BOE-XUDLERD.csv
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Churn_Modelling.csv
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Electric_Production.csv
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Electricity Consumption.csv
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FARS_onehot.csv
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Golf_Play_Train
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Height_Weight_Dataset.csv
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Holt_Winter_dailysales.csv
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iris.csv
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Mall_Customers.csv
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Market_Basket_Optimisation.csv
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mercedesbenz.csv
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monthly-milk-production.csv
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Movie_Id_Titles.csv
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movie_metadata.csv
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mtcars.csv
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mtcars_for_manymerge.csv
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Online_Retail
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pacific.csv
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Recommend.csv
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Salary_Data.csv
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sales-cars.csv
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shampoo.csv
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Social_Network_Ads.csv
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Solar Data Set.csv
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Time Series Sales By Store.csv
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Time_Series_Stock_Price.csv
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Time_Series_Temp_Data.csv
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trans_us.csv
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u.data
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Wine.csv
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