DevML

Table of Contents

• Introduction
• Regression with multiple Algorithms (Regression/ NN/ XGboost)
• Classification with multiple Algorithms(Logistic Regression/ NN/ XGboost)
• Regression with Random Forest
• Anomaly Detection k means
• Anomaly detection with Eliptic Envelope
• Market Basket Analysis
• Novelty Gift Analysis
• House Prices Outlier Detection
• My Decision Tree Implementation
• Feature Engineering Example
• Face detection with DLIB
• Image classification with CNN
• Other computer vision notebooks
• C++ Image Services API
• Infrastructure
• Datasets
• My Toolkit

Introduction

I am a seasoned software engineer with over a decade of experience in designing and developing robust software solutions, now fully dedicated to the fields of AI and ML.

My Toolkit

This repository contains multiple Jupyter notebooks written in Python. Mostly used libraries are Pytorch, XGboost, scikit-learn, Matplotlib, Pandas and Numpy