A temporal and spatial study of crime committed in Chicago
- Data cleaning, data manipulation, visualization, checking data quality
- PCA, K-Means Clustering, Extra Tree Classifier, Recursive Feature Selection, etc.
- Fitting Neural Network Model, Random Forest Model, Logistic Model, etc.
- Comparison using Confusion Matrix, ROC, AUC, etc.
- Checking Oversampling/Under Sampling, Predict the future Arrest Counts
- Research paper review, develop the research methodology, research report writing, creating poster, presenting the summary
Computational Issues and Hyper Parameter optimization in LSTM
- Data Preprocessing, dividing data into training set and validation set for optimizing the hyper-parameter using k-fold cross validation.
- Implementing Single LSTM, Stacked LSTM, Bidirectional LSTM, and CNN-LSTM model to this data set separately for hyper-parameter searching.
- Compared model performance and computational time using different optimizer, hidden size, learning rate, dropout rate, batch size, embedding vector size etc.
- Research paper review, develop the research methodology, report writing, creating poster, presentation.
Daily Crime Data in Chicago for the year 2012-2017
- Data cleaning, data manipulation, visualization, checking ACF, PACF, PCA, etc.
- Checking/removing Seasonality, Fitting SARIMA, Neural Network, Holt-Winters, etc. Models, compare models using RMSE, MAPE, Residual Analysis etc.
- Short term forecast, Long term forecast about the future crime
- Research paper review, develop the research methodology, research report writing, presenting the summary
Variational Bayesian Inference for Multivariate Normal Distribution
- Generate random data points from standard normal distribution with known covariance
- Generate mean and covariance for conjugate prior normal distribution, obtain the true posterior mean analytically
- Employ ADVI using statistical software, RStan
- Approximate posterior, calculate means and bias, compute statistics for bias
- Research paper review, develop the research methodology, poster presentation
How does Sepal Width, Petal Length, Petal Width explain Sepal Length in different species of iris plant?
- Checking/Removing Outliers, Influential Observations, Collinearity, Residual Analysis, Sensitivity Analysis
- Finding the best model that can explain the maximum variability by R-Squared, Adjusted R-Squared
Factors that determine the Gasoline Consumption
- Checked the assumptions of multiple linear regression model and transformed the data for violation of any assumptions
A Study on Improving Livelihood of Rural Women Through Income Generating Activities in Bangladesh
- Hands-on experience in collecting primary data, designing the framework of the questionnaire and analyzing those data to deliver valid inferences for assessing the overall status of rural women
