top of page ## Classification Models

Python

Top 6 machine learning algorithms (decision tree, random forest, naive bayes, KNN, SVM, logisitc regression) and how to build a machine learning model pipeline to address classification problems in python.

## Deep Learning

Python, TensorFlow

Deep learning is a sub-category of machine learning models that uses neural networks. To build a Deep Learning Model, it follows the procedure of prepare, define, compile, fit and evaluate the model.

## Exploratory Data Analysis (EDA)

Python

Main EDA techniques: univariate analysis, multivariate analysis, and feature engineering ... visit "Semi-Automated Exploratory Data Analysis Process in Python" for full code walk-through.

## Linear Regression

Python

This notebook provides a practical guide to implement linear regression, walking through the model building lifecycle: EDA, feature engineering, model implementation and model evaluation. Please visit article "A Practical Guide to Linear Regression" for step by step guide.

## Logistic Regression

Python

This is a step by step guide of implementing Logistic Regression model using Python library scikit-learn, including fundamental steps: Data Preprocessing, Feature Engineering, EDA, Model Building and Model Evaluation.

## Recommendation System

Python

This code snippet includes the procedure of building a recommender system using KNN and SVD: 1. EDA for Recommender System 2. Collaborative Based Filtering Algorithms: K Nearest Neigbour vs. Singular Value Decomposition; 3. Model Evaluation: cross validation vs. train-test split; 4. Provide Top Recommendations

## Regression Models

Python

This code snippet includes the comparison of  four common types of regression models: Linear Regression, Lasso Regression, Ridge Regression, Polynomial Regression

## Statistical Power

Python

Code snippet for an interactive guide to Statistical Power. A visual illustration of the relationship among Power, Type 1 error and Type 2 error.

## Statistical Tests

Python

An interactive exploration that compares and visualizes the difference between three common statistical tests: T-test, ANOVA test and Chi-Squared test.

## Time Series Analysis

Python

This code snippet covers ARMA, ARIMA and SARIMA models for time series analysis. Additionaly, explore concepts and techniques related to time series data, including Stationarity, ADF test, ACF/PACF plot and AIC.

Python, Streamlit

This code snippet covers following three steps to get your hands on building your first web app and extend your data analytics projects to a self-served platform:

• Extract Data and Build Database

• Define Data Analytics Process as Functions

• Construct Web App Interface

More Coming Up ...

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