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Python, TensorFlow

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. 

Python

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. 

Python

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.

Python

Regression Models

Python

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

Python

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.

Python

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

Python

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.

Python

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.


Python

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.

Python

Data Transformation

Python

Log transformation, clipping methods, minmax scaler, standard scaler and robust scaler, visit Data Transformation and Feature Engineering in Python for full code walk-through.

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