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Customer Churn Prediction - My Intership Project End to End From Scratch

Pull and process raw data from the database, create a new data table at the customer level from raw data, make customer behaviour, demographics and product journey analysis, make customer segmentation from insight gathered, and make customer churn modeling to predict customers who will churn...

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Medical Cost Personal - Predict Insurance

Through this project, we are trying to help insurance companies to predict the cost of insurance premiums based on the background of the insurance beneficiary. With the limited availability of features, the resulting model can provide a fairly good performance.

Fajar Tirtayasa

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Anomaly detection with IsolationForest

Project to analyse anomalies spent by corporate credit cards of Brazilian government.

Guilherme Ludwig

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Formality Neural Machine Translation

Our project aims to use and compare Neural Machine Translation models for translation of informal English sentences to formal English sentences. Initially, we imagined this functionality to be useful for new English speakers who are trying to navigate the way native English speakers speak...

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Secure the Bag

A platform designed for users to gain a deeper understanding of food insecurity in California. Predictive models are used to create data visualizations demonstrating the historical and future trends in food security in California. Tools for machine learning implemented to have users interact and...

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Academic Publications

Mitigating Dataset Artifacts in Natural Language Inference Through Automatic Contextual Data Augmentation and Learning Optimization (LREC 2022 - Main Author), CLFD: A Novel Vectorization Technique and Its Application in Fake News Detection (LREC 2020 - Main Author).

Michael Mersinias

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Germany Rental

It's very hard for foreigners like me to find an apartment in Germany and we actually don't know how much do we have to pay per month. So, I dig deep in analysis, clean, virtualization, and creating a model by using Light Gradient Boost (similar to XGBoost but faster!) to predict the rental...

Patawee Ratanaruengwatna

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Spanish Train

Rail transport in Spain operates on four rail gauges and services are operated by a variety of private and public operators. The total route length in 2012 was 16,026 km (10,182 km electrified). I'm trying to analyze the trend of the train usage through by using time as the index. We could know...

Patawee Ratanaruengwatna

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Upskilling with Ubiqum Code Academy

A 500-hours project-based course where the students develop and hone hands-on skills in Data analysis, Data visualisation and Machine Learning modelling with a variety of tools and programming languages (part-time, until end of March 2022). This is equipping me with the necessary skills and...

Alexandra Florea

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Customer Churn Prediction

Created an interpretable model that predicts churn on telecom data found on Kaggle (F1: 0.796) to build a pipeline to try and retain more customers. Used SMOTE to oversample minority class (churned customers) which improved the F1 score from 0.61 to 0.80. Engineered new features, for example,...

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Student Performance Predictor Application

• End-to-end application that predicts the student performance based on his/her prior educational and geographic records. The dataset was created synthetically for training and analyzed using seaborn library. • The application was built using Python and trained using a Random Forest model and...

Rashmi Badadale

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Sales Forecast Model

Forecasting product sales with Facebook's Prophet library and Modeltime R package.

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Using ML to predict how much your car will cost

Created a web app that predicts the selling price of your used car in dollars based on features such as age, odometer value, gear and vehicle type etc. Cleaned and analyzed a dataset of used cars sold on Craigslist, applied and compared between different regression models such as XGBoost and...

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Access to the education around the world

In this project, data are collected from different databases. The main objective was to produce a dashboard and segmentation to explain the differences in access to school around the world. Clustering algorithms are used and 4 groups were found. With the help of these clusters, we can imagine...

Cécile Guillot

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2019 NBA Final: Twitter Analysis

An Analysis of Tweets posted during 2019 NBA Finals with Infographics.

Edoardo Gervasoni

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Kepler Exoplanet Classification

Preprocessing, exploration and classification of the data collected by the NASA-build satellite Kepler Space Observatory with the objective of finding exoplanets.

Edoardo Gervasoni

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Causes of Employees' Attrition

Exploring the causes of employees' attrition through the analysis of Directed Acyclic Graphs and the implementation of Structure Learning Algorithms.

Edoardo Gervasoni

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Energy Price Forecasting

Forecasting of the price of the Energy market through linear (ARIMA, UCM) and non linear (KNN, RNN) models.

Edoardo Gervasoni

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Salary Prediction in Tech Jobs

How much should someone earn based on level education and experience? Despite the fact that salary may not always be the primary motivation for accepting a job offer or staying in a role. The objective is to make accurate salary predictions based on existing known salaries by job and location....

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RFM Customer Segmentation

RFM segmentation allows marketers to target specific clusters of customers with communications that are much more relevant for their particular behavior – and thus generate much higher rates of response, plus increased loyalty and customer lifetime value. Like other segmentation methods, RFM...

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