ransomk,Ransom,github

👋 Hi, I’m @Ransomk
👀 I’m interested in Data Science, Technology, Finance, Video games, Art, Pop Culture, Memes
🌱 I’m currently learning Data Science
💞️ I’m looking to collaborate on Data Science and data analysis projects
📫 How to reach me. Holla at me on my email - [email protected]

Ransom's Projects

30-days-of-react-fork

30 Days of React challenge is a step by step guide to learn React in 30 days. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw

andrew-ng-notes

This is Andrew NG Coursera Handwritten Notes.

california-housing-price-prediction

A simple data science project on the California Housing Dataset with some Exploratory data analysis and use of Linear Regression models from sklearn and Seaborn plots

capstone-data-science-course-project

This was a comprehensive project completed as part of the Data Science PG Programme. This covers classification algorithms over a dataset collected on health/diagnostic variables to predict of a person has diabetes or not based on the data points. Apart from extensive EDA to understand the distribution and other aspects of the data. Pre-processing was done to identify data which was missing or did not make sense within certain columns and imputation techniques were deployed to treat missing values. For classification the balance of classes was also reviewed and treated using SMOTE. Finally models were built and compared for accuracy on various metrics.Lastly the project contains a dashboard on the original data using Tableau

machine-learning-algorithms

One notebook to learn it all - Algorithms from scratch

ml-berlin-tutorial

IPython notebooks and data for scikit-learn tutorial at the ML Berlin Meetup.

nlp-course-project-review-analysis-and-topic-modeling-with-lda

This project includes analysis of buyer's reviews/comments of a popular mobile phone from an e-commerce website . Analysis done for the project include pre-processing of text data such as word-tokenisation, lemmatisation. Followed by Topic-modeling using Latent Dirichlet Allocation, POS tagging, and topic interpretation for business use

pca-and-xgboost-regression-mercedes-benz-test-data

A project based on Mercedes Benz test bench data for vehicles at the testing and quality assurance phase. Data consists of high number of feature columns. Key highlights from the project include - Dimensionality reduction using PCA and XGBoost Regression used after the dimensionality reduction to predict the time required to test the vehicles.