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ab_testing

Facebook has two different ways of bidding ads. These are called "maximum bidding" and "average bidding". The average bidding method of these two methods is the new one. We will find out whether the conversion rate of the new feature is higher than the old one by applying AB testing.

arl

ARL is a rule based algorithm. It is discovering pattern of items, products or movies. In this script we will examine products in the online retail dataset.

crm_analytics

In this section, we will analyze important metrics related to crm analytics such as level based persona, rfm metrics, customer lifetime value calculation, customer lifetime prediction.

feature_engineering

This is a part of the data analytics and machine learning process that data scientists spend most of their time on. In this repo, we will dive into the topics respectively OUTLIER HANDLING, MISSING HANDLING, ENCODING, FEATURE SCALING, FEATURE EXTRACTION.

recommendation_systems

A recommender system is an application of machine learning that predicts the future preference of a set of products for a user and provides personalized suggestions. This script is a practical introduction to the main Recommender System (RecSys) techniques.

sentiment_analysis

Sentiment analysis is a natural language processing (NLP) technique used to determine whether data is positive, negative or neutral. Sentiment analysis models focus on polarity (positive, negative, neutral) but also on feelings and emotions (angry, happy, sad, etc), urgency (urgent, not urgent) and even intentions (interested v. not interested).

tableau

time_series

A time series is a series of data points over time. Time series forecasting is the use of a model to predict future values based on previously observed values.

unsupervised_learning

In unsupervised learning, a dataset is provided without labels, and a model learns useful properties of the structure of the dataset. It uses machine learning algorithm to analyze and cluster unlabeled datasets.