Experienced scientist with over five years of experience in large-scale big data research with a keen eye for aesthetic excellence in communicating results intuitively to stakeholders. Eager to transfer scientific rigor, relentless work-ethic, and excellent team working skills into powerful data science that offers actionable insights to inform and guide successful managerial decision-making.

Given by my career in academic research, my daily activities involed advanced statistical analysis in R. While I cannot share these projects publically, here's a compilation of Python data science projects I've undertaken for educational purposes. While I used multiple packages within each, I highlighted some packages, whose power the project highlights. Feel free to click on the project name to explore the details of each project.

ID	Project Name / Dataset	Data Science Concepts Showcased	Package in Focus	Module	Function(s)
1	US Medical Insurance Cost	Exploratory Data Analysis (EDA)	numpy, pandas		misc.
2	Life Expectancy & GDP	Data Visualization	matplotlib, seaborn		misc.
3	Stock Price Prediction	Linear Regression	sklearn	.linear_model	LinearRegression()
4	Census Income (LogReg)	Logistic Regression	sklearn	.linear_model	LogisticRegression()
5	Breast Cancer	K-Nearest Neighbors (KNN) Classification	sklearn	.neighbors	KNeighborsClassifier()
7	Flags	Decision Trees (incl. pruning)	sklearn	.tree	DecisionTreeClassifier()
8	Obesity	Wrapper Methods	mlxtend	.feature_selection	SequentialFeatureSelector() [SFS, SBS], RFE()
9	Wine Qualiy	Regularization	sklearn	.linear_model	LogisticRegressionCV()
10	Raisins	Hyperparameter Tuning	sklearn	.model_selection	GridSearchCV(), RandomizedSearchCV()
11	Particles	Principial Component Analysis	sklearn	.decomposition	PCA()
12	Census Income (RanFor)	Random Forest Classification	sklearn	.ensemble	RandomForestClassifier(), BaggingClassifier(), RandomForestRegressor()
13	Census Income (Boosting)	Boosting	sklearn	.ensemble	AdaBoostClassifier(), GradientBoostingClassifier()
14	Book Recommender	Recommender System	surprise		KNNBasic()
15	Strike Zone	Support Vector Machines	sklearn	.svm	SVC()
16	Email Similarity	Naive Bayes Classification	sklearn	.naive_bayes	MultinomialNB()
17	Logic Gates	Perceptrons	sklearn	.linear_model	Perceptron()

Here's also a compilation of Python deep learning projects I've undertaken for educational purposes. Current focus lies on exploring tensorflow/keras and pytorch at depth. Feel free to click on the project name to explore the details of each project.

ID	Project Name	Deep Learning Concepts Showcased	Package in Focus	Module	Function(s)
1	Predicting Graduate Admission	Simple Regression/Prediction using Deep Learning	tensorflow	.keras	KerasRegressor / output activation = 'linear'
2	Predicting Life Expectancy	Simple Regression/Prediction using Deep Learning	tensorflow	.keras	KerasRegressor / output activation = 'linear'
3	Predicting Heart Failure	Simple Classification using Deep Learning	tensorflow	.keras	KerasClassifier / output activation = 'softmax'
4	Neural Machine Translation (NMT)	Long short-term memory networks (LSTMs)	tensorflow	.keras	LSTM()
5	Classifying Galaxy Images	Convolutional Neural Networks	tensorflow	.keras	Conv2D(), MaxPooling()
6	Classifying X-rays	Convolutional Neural Networks / Computer Vision	tensorflow	.keras	Conv2D(), MaxPooling()
7	Classifiying Cat Images	Transfer Learning with pre-trained neural networks	(py)torch		nn.Linear()
8	Multi-Layer Perceptron	MLP: modern feedforward fully connected artificial NN	(py)torch		self defined class Net(nn.Module)
9	Image Classification, CIFAR10	Math of dimension transformation within CNN	(py)torch		Conv2d(), relu(), pool(), dropout(), Linear()
10	Sentiment Analysis Movie Reviews	Sentiment Analysis with Recurrent Neural Networks	(py)torch		misc.

Here's also a compilation of Python natural language projects I've undertaken for educational purposes. Feel free to click on the project name to explore the details of each project.

ID	Project Name	NLP Facet Showcased	Package in Focus	Module	Function(s)
1	Classical Texts	Language Parsing	nltk		RegexpParser()
2	Mystery Friend	Bag-of-Words Language Quantification	sklearn	.feature_extraction.text	CountVectorizer()
3	News Content	Term Frequency-Inverse Document Frequency (tf-idf)	sklearn	.feature_extraction.text	TfidfTransformer(), TfidfVectorizer()
4	Presidential Vocabulary	Topic Modelling (Word Embeddings)	gensim	.models	Word2Vec()
5	Multi-Topic Chatbot	Rule-based chatbot using regex	re		match()
6	Denver Broncos Restaurant Chatbot	Retrieval-based chatbot using topic modelling	misc.	misc.	TfidfTransformer(), Word2Vec()
7	Generative Chatbot	Generative chatbot using topic modelling	misc.	misc.	TfidfTransformer(), Word2Vec()

In addition, I am currently working on extending my knowledge on machine learning engineering. Feel free to click on the project name to explore the details of each project.

ID	Project Name	ML Facet Showcased	Package in Focus	Module	Function(s)
1	Hierarchical Classes	Hierarchical Classes, Object-Orienter Programming	-	-	__ init __, __ repr __, .methods()
2	ATM Logging	Logging	logging	Stream/FileHandler, etc.	logger()
3	Surf Shop	Unit Testing	-	unittest	self.assertRaises, self.subTest(), self.assert..
4	Concurrent Programming	Sequential, Async, Threading & Multiprocessing Progamming	-	threading, asnycio, multiprocessing	Thread(), Process()
5	Bone Marrow Disease Classification	Machine Learning Pipelines	sklearn	pipeline	Pipeline(), ColumnTransformer()

Beyond coding for educatioanl purposes, I do enjoy coding for fun in my free time. Here's a compilation of projects I've undertaken with various objectives. Again, feel free to click on the project name to explore the details of each project.

ID	Project Name	Objective	Language	Package in Focus	Function(s)
1	Hierarchical Bayesian multinomial logit analysis	Create lighthouse/sawtooth report content and structure of hierarchical Bayes logistic regression analysis	R	ChoiceModelR
2	NFL Stats	Scrape NFL stats from the official website for the 2023 season, covering multiple categories	Python	.bs4	BeautifulSoup()

Here's a selection (in alphabetic order) of the packages/platforms/libraries I have worked with over the years: