This repository contains all the basic data science concepts with their implementations and and resulting outputs. All the following tasks are implemented using python in the repository , you can try this with any other languages like R, Matplotlib,etc. Which includes the following tasks:
#1: Basics of Coding R/Python
1. Using Comments R/Python
2. Executing Commands R/Python
3. Importing Packages R/Python
4. Getting Data into R
5. Saving Output R/Python
6. Accessing Records and Variables R/Python
#2: DATA PREPARATION
1. How to Add an Index Field Using R/Python
2. How to Change Misleading Field Values Using R/Python
3. How to Re Express Categorical Field Values Using R/Python
4. How to Standardise Numeric Fields Using R/Python
5. How to Identify Outliers Using R/Python
#3: EXPLORATORY DATA ANALYSIS
1. How to Construct a Bar Graph with Overlay Using R/Python
2. How to Construct Contingency Tables Using R/Python
3. How to Construct Histograms with Overlay Using R/Python
4. How to Perform Binning Based on Predictive Value Using R/Python
#4: DATA PREPARATION PHASE TO MODEL THE DATA
1. How to Partition the Data R/Python
2. How to Balance the Training Data Set R/Python
3. How to Build CART Decision Trees Using R/Python
4. How to Build C5.0 Decision Trees Using R/Python
5. How to Build Random Forests R/Python
#5: MODEL EVALUATION
1. How to Perform Model Evaluation Using R/Python
2. Accounting for Unequal Error Costs Using R/Python
#6: NAÏVE BAYES CLASSIFICATION
1. Demonstrate application of Naïve Bayes Using R/Python
#7: NEURAL NETWORKS
1. Demonstrate application of NEURAL NETWORKS using R/Python
#8: CLUSTERING
1. Demonstrate application of k‐MEANS CLUSTERING Using R/Python
#9: REGRESSION MODELLING
1. Demonstrate Estimation Model Evaluation Using R/Python
2. Demonstrate Stepwise Regression Using R/Python
#10: DIMENSION REDUCTION DIMENSION REDUCTION
1. Demonstrate How you will Identify Multicollinearity R/Python
2. Demonstrate HOW you’ll apply PRINCIPAL COMPONENTS ANALYSIS Using
R/Python
#11: LOGISTIC REGRESSION MODELLING
1. How to Perform Logistic Regression Using R/Python
2. How to Perform Poisson Regression Using R/Python
#12: ASSOCIATION RULES
1. How to Mine Association Rules Using R/Python
2. How to Apply the Confidence Difference Criterion Using R/Python
3. How to Apply the Confidence Quotient Criterion Using R/Python