This repositry contains notebook files which includes fundamentals of data processing, how to handle data using numpy and pandas, how to visualize data using matplotlib and seaborn, and a basic intro into image classification by building a simple CNN model.
It also has a collection of notebooks of machine learning algorithms classified into supervised and unsupervised learning.
- Linear Regression
- Logistic Regression
- Decision Tree
- Naive Bayes
- K Nearest Neighbors(KNN)
- K Means Clustering
- Principal Component Analysis(PCA)
The above algorithms are implemented using built in library functions. Additionally it also includes basic regression and classification tasks using Neural Networks(NN) and Multi Layer Perceptron(MLP).
Multinomial Naive Bayes classifier is used for Language Detection.
LSTM(RNN - Recurrent Neural Network) used for Microsoft Stock Price Prediction.
Gold Price and Diabetes Prediction using simple neural network.