data scientist | machine learning engineer
Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured and unstructured data. Data science is a concept to unify statistics, data analysis, informatics, and their related methods in order to understand and analyze actual phenomena with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. Services include but are not limited to:
Machine learning programs can perform tasks without being explicitly programmed to do so. It involves computers learning from data provided so that they carry out certain tasks. As a scientific endeavor, machine learning grew out of the quest for artificial intelligence. In the early days of AI as an academic discipline, some researchers were interested in having machines learn from data. They attempted to approach the problem with various symbolic methods, as well as what was then termed "neural networks"; these were mostly perceptrons and other models that were later found to be reinventions of the generalized linear models of statistics. Probabilistic reasoning was also employed, especially in automated medical diagnosis. Services include but are not limited to:
Formerly the Director of Development for a non-profit that supported both social and educational justice in the third world, I currently serve as an educator in the aforementioned fields and courses listed below. In just two years, I have tutored undergraduate students from the University of Toronto, Simon Fraser University, Purdue University, the Universities of Illinois, Michigan, North Carolina, and Southern California, taught graduate and post-graduate students from the Massachusetts Institute of Technology, California Institute of Technology, Columbia University, Hong Kong University of Science and Technology, and the Indian Institutes of Technology, as well as worked collaboratively with executives from J.P. Morgan Chase and the Walmart Corporation.
Nuveen Sales Regression and Lift Analysis Slide Deck
Super Store
Segmentation and RFM Analysis using Kmeans
Segmentation Revisited: Keyword Extraction to Ensemble Voting
Resume Screening
with Word Frequency and KNN
Salary Prediction with Feature Engineering and Random Forest
Employee Retention
A/B Testing and Regression Models
Breast Cancer
Exploratory Data Analysis
Brain Tumor
Classification with ResUNet
Covid and Pneumonia
Chest X-ray
Multi-Classification
Behavioral Risk Factors
and the US Census
Citibike
EDA and Maintenance Prediction
Singapore
GDP and Healthcare Analysis
NYC
Property Sales and Investments
Stock
Dashboard
Loan Prediction
with Recursive Feature Elimination and XGBoost
Credit Risk Modeling
Portfolio Optimization with
TensorFlow and D3
Chicago Air Quality Dashboard
EDA using D3
India
Air Quality Prediction
Human Activity
Classification and Prediction
Indian
Passengers per Flight
Prediction
Indian Airline Fare
Prediction
Forecasting Sales
ARIMA to Facebook Prophet
Worldwide Power Consumption
LSTM Prediction
New Orleans Police Department
Bodycam Data with Mapbox Template
Vehicle Routing Problem
Case Study with OR-Tools
Keyword Extraction
using NLTK
Next Word Prediction
NLTK and LSTM
Text Summarization
with PageRank
Text Summarization
Regex and NLTK
Consumer Complaints
Part 1
Consumer Complaints
Part 2
Consumer Complaints
Part 3
Image Analysis
using Kmeans Clustering
Harrison Corners Algorithm
from Scratch
Image Stitching
with OpenCV
Optical Flow with
Lucas-Kanade Algorithm from Scratch
Face Detection with
HAAR Cascade Classifier
Facial Expression Recognition
Keras
Facial Expression Recognition
PyTorch and ResNet
Object Character Recognition
with PyTesseract
Point and Click
Image Segmentation
Chess Openings
Part 1
Chess Openings
Part 2
Chess Openings
Part 3
AlphaBeau
Coming Soon...
Infinite Shakespeare
Coming Soon...
principal consultant & project manager
I am a data scientist and machine learning consultant who prides himself on the principles of perpetual education, humanism, and futurism. As a passionate student of both hard and soft sciences, I believe in an interdisciplinary and interpersonal approach to problem-solving.
According to Andrew Ng, a pioneer of online education and neural networks, "AI is the new electricity." The rise of electricity transformed every major industry, and in so doing, transformed every culture and the face of our world. We are witnessing the proliferation of AI at an even faster rate. As a witness to the power of this technology and the breadth of its application, I am joining the effort to "democratize deep learning."
As a professional consultant and project manager, I help clients better understand their own data vis-à-vis how it's collected, structured, and processed. With the clients' domain knowledge and my personal guidance, we decide what business solutions are "machine learnable" as well as scalable for sustainable growth. It has been my passion and privilege to work across industries educating fellow team members about artificial intelligence as we learn how to build a better world together.
