README.md

README.md

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 ### Portfolio Projects
 - GIS & Spatial Analysis:
- - Title: ["Examining Geospatial Covariate Relationships with Civilian Killings in South Sudan’s Civil War"](./GIS/GIS_covariate_relationships-killings-south_sudan.html)
+ - Title: [**"Examining Geospatial Covariate Relationships with Civilian Killings in South Sudan’s Civil War"**](./GIS/GIS_covariate_relationships-killings-south_sudan.html)
  - Focus: Geospatial Statistics
  Technology Used: QGIS, R, GeoDa
  - Contents: Geospatial interpolation, hot spot analysis, Moran's I calculation, Moran's I residual analysis, Lagrange Multiplier (LM) and Robust LM lag and error diagnostics, and Spatial Durbin models.
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  - Technology Used: R Markdown, ggmap, tmap, sp, sf, rgdal, stadia/stamen maps, plotly, dplyr, ggplot2, ggthemes, ggpubr, stringr, scales, and kableExtra
  - Contents: Interactive and static charts, GIS maps, heat map tables, density maps, and union buffers and using statistics within them
 - Natural Language Processing (NLP):
- - Title: ["Using News Articles on Events in Nigeria in 2019 to Predict Political Violence"](./ML-Predicting%20Violence%20with%20News/Using_Nigerian_News-based_ML_Models_to_Predict_Political_Violence.html)
+ - Title: [**"Using News Articles on Events in Nigeria in 2019 to Predict Political Violence"**](./ML-Predicting%20Violence%20with%20News/Using_Nigerian_News-based_ML_Models_to_Predict_Political_Violence.html)
  - Focus: NLP for Time-Series Forecasting
  - Technology Used: Python, TF-IDF word transformation, NLTK library, Scikit-Learn machine learning models, Scikit-Learn's TimeSeriesSplit, Augmented Dickey-Fuller Test, first-differencing, lags
  - Contents: Converting news articles by publishing date into time-series machine elarning forecasting models. Performance comparison between Ridge, Lasso, Random Forest, and XGBoost regression models