All Kaggle competition entries, plus more.
Created a Random Forest Descision Tree Classifier for training and evalutaion of the dataset using Sckit-Learn, this is one of easier ways of implementing a classifier and it works pretty well for most of the part if the huge variety of data is available. Achieved 77.03% of accuracy.
Created a Deep Neural Network Classifier for training and evalutaion of the dataset using TensorFlow, this is once again one of the most popular beginning projects for people who are interested in Deep Learning. Achieved 96.97% of accuracy.
Created a Random Forest Descision Tree Classifier for training and evalutaion of the dataset using Sckit-Learn, the decision tree classifier created in this project was deeper than the ealier project whose name is resembles.