Sunil Hariharan's repositories
amazon-sagemaker-examples
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
Antallagma-Trade-Forecast
Used linear regression, XGBoost , Naive forecast, simple moving average, exponential moving average and time series model ARIMA to forecast the number of sales as well as the price
dbgui
GUI for inserting,deleting and updating records in the sqlite3 database
dbgui_with_login
A gui for inserting records into database for the faqbot that i developed along with a login form and standalone executable file
diabetes_prediction
used linear regression to predict the diabetes level
dlaicourse
Notebooks for learning deep learning
faq12
app module solution issue flow
faq8
app solution issue workflow
hackathon_startupfunds
done extensive eda to get insights and applied binning,linear regularization with heavy regularization,decision tree and finally a random forest
housing_dataset
used linear regression to predict the sales price of house...also done feature engineering...also found out the most important features
ocr
Extract specific text from scanned pdf documents
olympic_project_new
New olympic dataset project
sarcasm_headlines
NLP model to predict whether the headline is sarcastic or not
segmentation_project
used k-means clustering for segmentation to make business sense out of dataset which had features like gender,age,income,spending score
sms-spam-classification
NLP, multinomial naive Bayes to do binary classification of sms as spam or ham
Urban_sound_classification
voice recognition using Keras sequential neural network models(dense and gru)