Data Science

Data Science is a process to extract insight from the data using Feature Engineering, Feature Selection, Machine Learning etc. to solve the real-world business problem.

Data science has an intersection with artificial intelligence but is not a subset of artificial intelligence.

Data Science is the Art and Science of drawing actionable insights from the data.

 

Applications:
Retail, Bank, E-Commerce, Healthcare, and Telecom, etc.

Python Library for Data Science

To solve the business problem using Data Science for that data gathering, cleaning and visualization must be done. For that bellow python library, you should learn first.

 

NumPy

Pandas

  • Pandas Series
  • Pandas DataFrame
  • Pandas Read_csv
  • Pandas Write csv File
  • Pandas Handling Missing Values
  • Pandas concat()
  • Pandas join()
  • Pandas append()
  • Pandas GroupBy
  • ……
  • Course in progress …

 

Matplotlib

  • Python Matplotlib 
  • Matplotlib Line Plot
  • Matplotlib Histogram
  • Matplotlib Bar Chart
  • Matplotlib Pie Chart
  • Matplotlib Scatter Plot
  • Matplotlib Subplot
  • Matplotlib Save Figure
  • Matplotlib Image Show
  • ……
  • Course in progress …

Feature Engineering

  • Best 6 Methods to Handling Missing Values/Data Smartly – Data Cleaning
  • One Hot Encoding & Dummy Variables | Categorical Variable Encoding
  • Feature Scaling – Standardization vs Normalization
  • Label Encoding vs Ordinal Encoding | Categorical Variable Encoding

Machine Learning Project

  • Machine Learning Project End to End: Student Mark Prediction
  • Directing Customers to Subscription Through Financial App Behavior 
  • Breast Cancer Detection Using Machine Learning Classifier
  • House Prices Prediction Advanced Regression Techniques | Kaggle 
  • Bangalore House Price Prediction Machine Learning Project till Deployment

Seaborn

  • Python Seaborn Tutorial
  • Seaborn Line Plot
  • Seaborn Histogram
  • Seaborn Barplot
  • Seaborn Scatter Plot
  • Seaborn Heatmap
  • Seaborn Pairplot
  • ……
  • Course in progress …

Statistics for Machine Learning

  • R Squared Regression Analysis

Machine Learning Algorithms

  • Linear Regression
  • Root Mean Square Error
  • Ridge and Lasso Regression
  • Polynomial Linear Regression
  • Support Vector Regression
  • Support Vector Machine (SVM) Classification
  • Decision Tree Classification
  • Decision Tree Regression
  • Random Forest Classification
  • Random Forest Regression
  • K Nearest Neighbor Classification
  • K Nearest Neighbor Regression
  • Naïve Bayes Classifier
  • Save & Load Machine Learning Model

Data Science course is going on…