Kaggle Competitions Guides and Solutions
Solutions and Guides to various Kaggle Machine Learning Competitions.
Guides and solutions are present in Jupyter Notebook format.
Programming Language: Python
Datasets are taken from Kaggle Competitions.
Trying out the following classifiers:
- Decision Tree
- Random Forest
- Support Vector Machine (SVM)
- Logistic Regression
- Linear SVC
- k-Nearest Neighbor (KNN)
- Naive Bayes
- Stochastic Gradient Decent (SGD)
Trying out the following regression models:
- Elastic Net
- Kernel Ridge
- Gradient Boost
Using Deep Learning with Keras - the Neural Network Library written in Python.
The following Neural Network models are used for this problem:
- Multi-layer Perceptron Model (MLP)
- Convolutional Neural Network (CNN) Model
Using Logistic Regression Model
Using Multiple Models: Logistic Regression, SGD, Naive Bayes, OneVsOne Models
Using Long short-term memory (LSTM) recurrent neural network (RNN) model for IMDB dataset
Using Long short-term memory (LSTM) recurrent neural network (RNN) model for Kaggle dataset