Project which will predict credit default or credit risk using artificial neural network algorithms. It will help banks and financial institutions to assign a credit score to the customer profile/portfolio and make a decision whether to sanction a loan or not
Little example of TensorFlowJS using a pre loaded Artificial Neural Network (ANN). 🧠
Implementation of Algorithms such as ANN, CNN, RNN, Boltzmann Machine, AutoEncoders. Time to go deep :)
FIPPS is a Flood Inundation Prediction and Projection System. It is a Theoretical model to predict inundation. It blends data sources, geospatial analysis, machine learning, and real-time data to predict and visualize flood extents accurately. FIPPS improves flood preparedness, disaster management, and public safety in flood-prone areas.
Multiple Regression, Ridge Regression, Lasso Regression, ElasticNet, Decision Trees (CART), Random Forest, XGBoost, LightGBM, Gradient Boosting, ANN, KNN Logistic Regression, SVM Hierarchical Clustering, K-Means , PCA
Full-stack Project which users can search stocks. This system can also do some predictions and show graphs of some stocks
In this project ANN model is build on the Prediction of HR Interview Analysis and Video Game SalesmAnalysis and CNN Model is build on Cats & Dogs Image Classification.
A project for NIR-based food quality modeling using PLS or ANN based on MATLAB or Python
Some introductory data science projects, along with code and documentation. Of course, these projects are university projects.
ANN, CNN dynamic model generation codes to classify Urban8K Audio Dataset.
This is a university project for my Data Mining course. This work focuses on a binary classification task (related to CS-GO); which team will win?
This will be a blog about AI and other related topics in the realm of science
A blog about the use cases and applications of ANNs
IndexLab is an internal tool for building, searching, and evaluating vector indexes
Early identification and treatment of thyroid disorders using predictive modeling. · Implemented Artificial Neural Networks (ANN), Support Vector Classifier(SVC), Random Forest, and XGBoost for risk prediction. · Developed a web application using ML Flask for user-friendly access to predictive models
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