Machine Learning & AI Foundations: Movies Recommendations Part 2

Recommendation systems are the important part of almost every modern consumer websites like Amazon and Netflix. The systems help drive customer interaction and sales by helping customers discover products and services they might not ever find themselves.   In this project, we use machine learning to solve recommendation problems. What you learn can then be…

Machine Learning & AI Foundations: Movies Recommendations Part 1

Have you ever wondering how Netflix know what movies you probably like? Or if you watch Stranger Things that Netflix is likely to suggest to you is the ET: The Extra-Terrestrial. Basic on the customer viewing behavior data, we can predict users discover the exact content they want to watch. Similar products method is one of the…

Tableau Project: Kickstarter Dataset

Kickstarter, the crowdfunding platform, is thinking about providing a consulting service to project founders to help its customers create more successful crowdfunding campaigns. By understanding some simple key performance indicators, you can run a successful campaign! To do some initial analysis, I used Tableau to complete the task and solving data problems.  Kickstarter dataset: http://bit.ly/2cgMGDm.…

Data Quality : Bank Consumer Database

Discovering whether data are of acceptable quality is a measurement task and not a very easy one. In this data quality project, I used excel and python to deal with Consumer Complaint Database, complaints about financial products and services.Data quality is important because, without high-quality data, you cannot understand or stay in contact with your customers.…

Database 1 : SQL Practice

Structured Query Language (SQL) is the language used to manipulate data in relational databases. In rSQUAREedge Certified Data Analytics Practitioner (CDAP) Program, I was luckily be taught by Sam Sultan ,director of Information Technology at Home Box Office (HBO). In the classes, we use SQL to select, update, insert, and delete data from database tables, and acquire hands-on experience…

Credit Risk Modeling in R

Use R to explore a real-life data set, then preprocess the data set such that it’s in the appropriate format before applying the credit risk models. First, I examed the dataset loan_data discussed in the video throughout the exercises in DataCamp. Goal: understand the number, percentage of defaults. To learn more about variable structures and spot unexpected…

Social Media Analytics with Python

We use  Twitter, Facebook, and Google social media to share our life experiences, initiate ideas and provide opinions in a free and open way. Businesses are hence interested in understanding what people think and say about their products and services. They are augmenting their business applications to extract, understand and analyze social media data about…