Transfer Learning and Fine-Tuning with TensorFlow

Application To Pneumonia Classification from X_ray Images

Transfer learning involves taking layers/learned features from a model trained on a larger dataset and using those features to initialize training on another similar task. Training deep learning models especially for computer vision requires massive data to perform well. Transfer learning allows models to be trained on smaller dataset by... [Read More]

Cost-Sensitive Deep Learning For Imbalanced Dataset Classification

Applied to Fraud Detection

Introduction Data with imbalanced target class occurs frequently in several domians such as credit card Fraud Detection ,insurance claim prediction, email spam detection, anomaly detection, outlier detection etc. Financial instituions loose millions of dollars every year to fraudulent financial transactions. It is important that these institutions are able to identify... [Read More]

Imbalanced Machine Learning For Fraud Detection

cost-sensitive xgboost,RusBoost,Smote,EasyEnsemble,cost-sensitive logistic regression

Introduction Data with imbalanced target class occurs frequently in several domians such as credit card Fraud Detection ,insurance claim prediction, email spam detection, anomaly detection, outlier detection etc. Financial instituions loose millions of dollars every year to fraudulent financial transactions. It is important that these institutions are able to identify... [Read More]

Automatic Machine Learning

automl in Python and R

Automated Machine Learning Automated Machine Learning (AutoML) has increased greatly the efficiency of building machine learning models. AutoML achieves this by automating in some applications data pre-processing ,feature engineering, feature extraction , feature selection and hyper-parameter tuning when building machine learning models. AutoML has also reduced the expertise in academic... [Read More]