Using Supervised ML Algorithms like KNN, Logistic Regression, Gaussian NB, SVM, Decision Trees, Random Forest, XGBoost and Deep Learning (Keras — Convolution Neural Network)
Breast cancer occurs when harmful (malignant) cancer cells are found in the breast tissues, it usually develops from the ducts in the breast. The cancerous cells may then spread throughout the breast and to other parts of the body.
Do you know that almost 1 in 16 women in Singapore will be diagnosed with breast cancer in their lifetime?
According to Gleneagles Hospital Singapore, breast cancer is the leading cause of cancer death in women today in Singapore. Fortunately, with earlier detection and improved treatment, more women are surviving the disease :)
Motivation / Objective
Using Collaborative Filtering Method — Alternating Least Squares (ALS)
Steam is one of the biggest video game digital service available in the market right now, with millions active users and accounts, hosting over thousands of computer games, which makes it an ideal platform for recommender system to be in place to facilitate consumers in their gaming experience.
As a fellow PlayStation / Nintendo gamer myself, I will probably try computer games at some point of time, therefore when Metis Project 4 comes along, it inspires me to create a recommender system to see what STEAM games will be recommended to…
Using Supervised ML Algorithms like KNN, Logistic Regression, Gaussian NB, SVM, Decision Trees and Random Forest.
Before I start on my model, this is just a little background on Cardiovascular Disease.
According to World Health Organization (WHO), Cardiovascular Diseases (CVD) is the Disorders of heart and blood vessels, and includes conditions like hypertension (high blood pressure) coronary heart disease (commonly known as heart attack). They are ranked as the number one cause of death globally.
One thing to note is that most Cardiovascular disease can actually be prevented by addressing behavioral risk factors such as smoking, obesity, physical inactivity and alcoholism. And this come to my motivation for my project.
Some of you guys might not…
First week into Metis Bootcamp (Singapore) as a data science student, I had to work on my very first project with my 3 online group mates and it was an exploratory data analysis of the MTA turnstile dataset. The goal was to utilize the MTA data set and recommend placement of street teams for a fictional non-profit organization (Women Tech Women Yes - WTWY) so they can get interested NYC commuters to sign up for their email list.
Approach
Our approach is to utilize the MTA turnstile data retrieved online for the period from July to August 2020 to recommend…
As an anime lover, I am always keeping a lookout for new anime recommendations, therefore for my Metis Project 2, I am intrigued to predict the anime rating scores based on the MAL website on Top Anime Ranking List.
Methodology
