Project data scientist

Project data scientist

ABOUT

Collection of practical, theoretical, and motivational ideas in data science, machine learning, and applied AI that I curated and created.

It aims to help someone learn, compare, and remember important concepts to use in their daily practice.

After completion, someone will have gained comprehension of and acumen for best practices, logical approaches, and inspiring ideas in data science, machine learning, and applied AI.

DOMAINS

Data science, machine learning, applied AI

CONTENTS

Industry methodologies and working frameworks, machine learning techniques, data pre-processing theories and good practice

This project is ongoing, check back soon for more.

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Case studies

Case studies

ABOUT

Collection of case studies in data science, machine learning, and applied AI that are self-initiated, self-taught, and that I autonomously carried out to completion.

It aims to help someone deliberately apply techniques, metrics, processes and everything in between to real-world problems with an emphasis on the strategic and tactical implications of the choices made at each step.

After completion, someone will have gained a reflex for strategic, tactical, and deliberate thinking about real-world problems.

DOMAINS

Fraud detection

TOOLS

Python, Pandas, Seaborn, NumPy, Matplotlib

TECHNIQUES

SVM (Linear), SVM (RBF), Decision Tree Classifier

This project is ongoing, check back soon for more.

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NLP starter

NLP starter

ABOUT

NLP Starter is a collection of fast fundamental NLP practice sets in Python that I designed and created. There’s a total of 3 NLP problems in this project.

It aims to help someone get started fast and gain a high-level understanding of the fundamental steps in the NLP lifecycle early on.

After completion, someone will have built intuition over the NLP lifecycle.

DOMAINS

Sarcasm detection in news headlines, Amazon product reviews, Google app reviews

TOOLS

Python, TensorFlow, Keras, Pandas, NumPy

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Deep learning starter

Deep learning starter

ABOUT

Deep Learning Starter is a collection of fast fundamental deep learning practice sets in Python that I designed and created. There’s a total of 6 classification problems in this project.

It aims to help someone get started fast and gain a high-level understanding of the fundamental steps in the deep learning lifecycle early on.

After completion, someone will have built intuition over the deep learning lifecycle.

DOMAINS / APPLICATIONS

Sign language recognition, handwritten digit recognition

TOOLS

Python, TensorFlow, Keras, Pandas, NumPy

Techniques

ANN, DNN, CNN

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Machine learning starter

Machine learning starter

ABOUT

Machine Learning Starter is a collection of fast fundamental machine learning practice sets in Python that I designed and created. There’s a total of 18 regression, classification, and clustering problems in this project.

It aims to help someone get started fast and gain a high-level understanding of the fundamental steps in the machine learning lifecycle early on.

After completion, someone will have built intuition over the machine learning lifecycle.

DOMAINS / APPLICATIONS

Price prediction, fraud detection, patient classification, customer segmentation

TOOLS

Python, sci-kit learn, NumPy, Seaborn

TECHNIQUES

Linear regression, KNN, decision tree classifier, SVM, random forest, K-means

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