Bulent Orun's Projects
[NeuralNet]Classifying handwritten digits with MNIST dataset
If you have already dealt with classification problems, you must have faced instances where one of the target class labels’ numbers of observation is significantly lower than other class labels. This type of dataset is called an imbalanced class dataset which is very common in practical classification scenarios.In this article, I’ll discuss the imbalanced dataset, the problem regarding its prediction, and how to deal with such data more efficiently than the traditional approach.
You’ve built your machine learning model – so what’s next? You need to evaluate it and validate how good (or bad) it is, so you can then decide on whether to implement it. That’s where the AUC-ROC curve comes in.
Breast Cancer Classification problem is analyzed on Wisconsin dataset . K-fold cross-validation is used to assess model performance. Algorithms are debugged with learning and validation curves.Fine Tuning techniques are applied via grid search CV.
Complete Guide to Regularization Techniques in Machine Learning
Coursera - CNN Programming Assignment: In this project, we will build a face recognition system with FaceNet. Face recognition is a method of identifying or verifying the identity of an individual using their face in photos, video, or in real-time
Feature Scaling for Machine Learning: Understanding the Difference Btw Normalization&Standardization
A collection of python Machine Learning articles and examples. You will find code related to Reinforcement Learning, Q Learning, MDP, Bellman, OpenAI solutions and others. You can watch our agents here http://bit.ly/2Ayj4vA
Code Repository for Perceptron Learning Algorithm
In this notebook,I implemented a YOLO on BCCD dataset consisting of cell images and I trained the YOLO for object detection / classification purposes.
In this notebook,I implemented a CNN on complex CelebA dataset consisting of face images and trained the CNN for smile classification using smile attributes of the pictures.
Resources for deep learning with satellite & aerial imagery
CICD_PracticeCode
Boosted neural network for tabular data